{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Preliminaries"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Datasets used: \n",
    "- `adult (Adult)` :<br>The UCI Adult dataset contains 14 features, which can be divided into two categories: demographic and income-related.<br> The demographic features include:\n",
    "\n",
    "    age: continuous.<br>\n",
    "    fnlwgt : continuous, represents final weight, which is the number of units in the target population that the responding unit represents.<br>\n",
    "    workclass: categorical, with values 'Private', 'Local-gov', 'Self-emp-not-inc', 'Federal-gov', 'State-gov', 'Self-emp-inc', 'Without-pay'.<br>\n",
    "    education: categorical, with values '11th', 'HS-grad', 'Assoc-acdm', 'Some-college', '10th', ..., '9th', 'Doctorate', '12th', '1st-4th', 'Preschool'.<br>\n",
    "    education-num: continuous with values 1 to 16, one number assigned to each label of education feature.<br>\n",
    "    marital-status: categorical, with values 'Never-married', 'Married-civ-spouse', 'Widowed', 'Separated', 'Divorced', 'Married-spouse-absent', 'Married-AF-spouse'.<br>\n",
    "    occupation: categorical, with values such as 'Machine-op-inspct', 'Farming-fishing', 'Protective-serv'.<br>\n",
    "    relationship: categorical, with values 'Own-child', 'Husband', 'Not-in-family', 'Unmarried', 'Wife', 'Other-relative'.<br>\n",
    "    race: categorical, with values such as white, black, and Asian.<br>\n",
    "    sex: categorical, with values male and female.<br>\n",
    "    \n",
    "    The income-related features include:<br>\n",
    "\n",
    "    hours-per-week: continuous.<br>\n",
    "    native-country: categorical, with values such as United-States, Mexico, and Germany.<br>\n",
    "    capital-gain: continuous, represent the amount of money an individual has gained from the sale of investments such as stocks, bonds, or real estate.<br>\n",
    "    capital-loss: continuous, represent the amount of money an individual has lost from the sale of investments such as stocks, bonds, or real estate..<br>\n",
    "    The target feature is the income, which is binary:<br>\n",
    "    income: categorical, with values less than or equal to 50K and greater than 50K.<br>\n",
    "\n",
    "Reference Links: https://archive.ics.uci.edu/ml/datasets/adult"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from pprint import pprint\n",
    "\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import classification_report, confusion_matrix, ConfusionMatrixDisplay\n",
    "\n",
    "import os\n",
    "import sys\n",
    "module_path = os.path.abspath(os.path.join('..', '..'))\n",
    "if module_path not in sys.path:\n",
    "    sys.path.append(module_path)\n",
    "\n",
    "import facts\n",
    "from facts.clean import clean_dataset\n",
    "from facts import valid_ifthens_with_coverage_correctness, rules2rulesbyif\n",
    "from facts.models import customLogisticRegression\n",
    "from facts.parameters import ParameterProxy\n",
    "from facts.formatting import recourse_report_reverse, print_recourse_report, print_recourse_report_cumulative, print_recourse_report_KStest_cumulative\n",
    "from facts.utils import load_rules_by_if, save_rules_by_if\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from IPython.display import Markdown, display"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "\n",
    "random_seed = 131313 # for reproducibility\n",
    "precomputed_rules_file = Path(\"..\") / \"..\" / \"Pre-computed Results\" / \"Adult\" / \"rulesAdult_race_atomic.data\"\n",
    "precomputed_rules_with_cumulative_file = Path(\"..\") / \"..\" / \"Pre-computed Results\" / \"Adult\" / \"rulesAdult_race_cumulative.data\""
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>Workclass</th>\n",
       "      <th>education-num</th>\n",
       "      <th>marital-status</th>\n",
       "      <th>occupation</th>\n",
       "      <th>relationship</th>\n",
       "      <th>race</th>\n",
       "      <th>sex</th>\n",
       "      <th>capital-gain</th>\n",
       "      <th>capital-loss</th>\n",
       "      <th>hours-per-week</th>\n",
       "      <th>native-country</th>\n",
       "      <th>income</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>(34.0, 41.0]</td>\n",
       "      <td>State-gov</td>\n",
       "      <td>13</td>\n",
       "      <td>Never-married</td>\n",
       "      <td>Adm-clerical</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>2174</td>\n",
       "      <td>0</td>\n",
       "      <td>FullTime</td>\n",
       "      <td>United-States</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>(41.0, 50.0]</td>\n",
       "      <td>Self-emp-not-inc</td>\n",
       "      <td>13</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Exec-managerial</td>\n",
       "      <td>Married</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>PartTime</td>\n",
       "      <td>United-States</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>(34.0, 41.0]</td>\n",
       "      <td>Private</td>\n",
       "      <td>9</td>\n",
       "      <td>Divorced</td>\n",
       "      <td>Handlers-cleaners</td>\n",
       "      <td>Not-in-family</td>\n",
       "      <td>White</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>FullTime</td>\n",
       "      <td>United-States</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>(50.0, 90.0]</td>\n",
       "      <td>Private</td>\n",
       "      <td>7</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Handlers-cleaners</td>\n",
       "      <td>Married</td>\n",
       "      <td>Black</td>\n",
       "      <td>Male</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>FullTime</td>\n",
       "      <td>United-States</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>(26.0, 34.0]</td>\n",
       "      <td>Private</td>\n",
       "      <td>13</td>\n",
       "      <td>Married-civ-spouse</td>\n",
       "      <td>Prof-specialty</td>\n",
       "      <td>Married</td>\n",
       "      <td>Black</td>\n",
       "      <td>Female</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>FullTime</td>\n",
       "      <td>Cuba</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            age          Workclass  education-num       marital-status  \\\n",
       "0  (34.0, 41.0]          State-gov             13        Never-married   \n",
       "1  (41.0, 50.0]   Self-emp-not-inc             13   Married-civ-spouse   \n",
       "2  (34.0, 41.0]            Private              9             Divorced   \n",
       "3  (50.0, 90.0]            Private              7   Married-civ-spouse   \n",
       "4  (26.0, 34.0]            Private             13   Married-civ-spouse   \n",
       "\n",
       "           occupation    relationship    race      sex  capital-gain  \\\n",
       "0        Adm-clerical   Not-in-family   White     Male          2174   \n",
       "1     Exec-managerial         Married   White     Male             0   \n",
       "2   Handlers-cleaners   Not-in-family   White     Male             0   \n",
       "3   Handlers-cleaners         Married   Black     Male             0   \n",
       "4      Prof-specialty         Married   Black   Female             0   \n",
       "\n",
       "   capital-loss hours-per-week  native-country  income  \n",
       "0             0       FullTime   United-States       0  \n",
       "1             0       PartTime   United-States       0  \n",
       "2             0       FullTime   United-States       0  \n",
       "3             0       FullTime   United-States       0  \n",
       "4             0       FullTime            Cuba       0  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "urlfile= \"https://raw.githubusercontent.com/columbia/fairtest/master/data/adult/adult.csv\"\n",
    "\n",
    "X = pd.read_csv(urlfile)\n",
    "df = clean_dataset(X, \"adult\")\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_binary(val):\n",
    "    if val in [\" Amer-Indian-Eskimo\", \" Asian-Pac-Islander\", \" Black\", \" Other\"]:\n",
    "        return \" Non-White\"\n",
    "    elif val == \" White\":\n",
    "        return val\n",
    "    else:\n",
    "        raise NotImplementedError(\"Code should be unreachable\")\n",
    "\n",
    "df.race = df.race.map(make_binary)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model training and test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "y = df['income']\n",
    "X = df.drop('income', axis=1)\n",
    "\n",
    "num_features = X._get_numeric_data().columns.to_list()\n",
    "cate_features = X.select_dtypes(include=['object','category']).columns.to_list()\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, train_size=0.7, random_state=random_seed, stratify=y)\n",
    "\n",
    "X_train = X_train.reset_index(drop=True)\n",
    "X_test = X_test.reset_index(drop=True)\n",
    "y_train = y_train.reset_index(drop=True)\n",
    "y_test = y_test.reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: total: 3.03 s\n",
      "Wall time: 3.1 s\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([0., 0., 1., 1., 0., 1., 0., 0., 1., 0., 0., 0., 1., 0., 0., 1., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 1., 0., 1., 0., 0., 0., 0., 0., 1., 0., 1., 1., 0., 0.,\n",
       "       1., 0., 1., 1., 0., 0., 0., 0., 0., 0., 1., 0., 0., 0., 1., 0., 0.,\n",
       "       1., 0., 1., 0., 0., 0., 1., 0., 1., 0., 1., 0., 1., 1., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 1., 0., 1., 1., 0., 0., 0.])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "model = customLogisticRegression(max_iter = 1500)\n",
    "model.fit(X_train, y_train, cate_columns=cate_features, target_column='income')\n",
    "model.predict(X_test.iloc[:100, :])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.88      0.93      0.90     10205\n",
      "           1       0.73      0.61      0.67      3362\n",
      "\n",
      "    accuracy                           0.85     13567\n",
      "   macro avg       0.81      0.77      0.78     13567\n",
      "weighted avg       0.84      0.85      0.84     13567\n",
      "\n"
     ]
    }
   ],
   "source": [
    "positive_label = 1\n",
    "negative_label = 0\n",
    "preds_Xtest = model.predict(X_test)\n",
    "print(classification_report(y_test.map({negative_label: 0, positive_label: 1}), preds_Xtest))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "[encoded data, 26516 characters]",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "conf_matrix = confusion_matrix(y_test, preds_Xtest)\n",
    "cm_disp = ConfusionMatrixDisplay(confusion_matrix=conf_matrix)\n",
    "cm_disp.plot()\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Main Contribution"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Find all valid if-thens with all respective coverages and correctness, for all subgroups.\n",
    "\n",
    "**Caution!** This step takes time. Uncomment the following block if you wish to run."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Computing frequent itemsets for each subgroup of the affected instances.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:01<00:00,  1.00it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Computing the intersection between the frequent itemsets of each subgroup of the affected instances.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "100%|████████████████████████████████████████████████████████████████████████| 25414/25414 [00:00<00:00, 413634.57it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Computing all valid if-then pairs between the common frequent itemsets of each subgroup of the affected instances and the frequent itemsets of the unaffacted instances.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████████████████████████████████████████████████████████████████████| 18812/18812 [00:03<00:00, 6006.09it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Computing correctenesses for all valid if-thens.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      " 63%|███████████████████████████████████████████████                            | 78747/125486 [26:42<14:01, 55.57it/s]"
     ]
    }
   ],
   "source": [
    "# ifthens_coverage_correctness = valid_ifthens_with_coverage_correctness(\n",
    "#     X_test,\n",
    "#     model=model,\n",
    "#     sensitive_attribute='race',\n",
    "#     freqitem_minsupp=0.01,\n",
    "#     missing_subgroup_val=\"Unknown\",\n",
    "#     drop_infeasible=True,\n",
    "#     drop_above=True\n",
    "# )\n",
    "\n",
    "# print(f\"Number of if-thens: {len(ifthens_coverage_correctness)}\")\n",
    "# rules_by_if = rules2rulesbyif(ifthens_coverage_correctness)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Use this for loading rules from disk\n",
    "rules_by_if = load_rules_by_if(precomputed_rules_file)\n",
    "\n",
    "## Use this for saving rules on disk\n",
    "#save_rules_by_if(precomputed_rules_file, rules_by_if)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you have `scikit-learn` version 1.0.2 installed, you can also run the below cell to load, additionally to rules, the model and test data we used."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# from facts.utils import load_object, save_object\n",
    "\n",
    "# ## Use this if you wish to load state (model, X_test, rules) from disk\n",
    "# (rules_by_if, X_test, model) = load_object(precomputed_rules_file)\n",
    "\n",
    "# ## Use this if you wish to save state (model, X_test, rules) on disk\n",
    "# # save_object(precomputed_rules_file, (rules_by_if, X_test, model))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "num_features = ['education-num', 'capital-gain', 'capital-loss']\n",
    "cate_features = ['age', 'Workclass', 'marital-status', 'occupation', 'relationship', 'race', 'sex', 'native-country']\n",
    "ord_features = ['hours-per-week']\n",
    "\n",
    "feature_weights = {\"race\" : 100 , \"sex\": 100, \"marital-status\": 5, \"relationship\":5, \"age\": 10, \"occupation\": 4, \"Workclass\": 2, \"native-country\": 4,\n",
    "                    \"hours-per-week\":2, \"capital-gain\": 1, \"capital-loss\":1, \"education-num\": 3}\n",
    "features_with_binary_cost = cate_features\n",
    "features_with_proportional_cost = num_features\n",
    "\n",
    "\n",
    "comparators = facts.feature_change_builder(\n",
    "    X_test,\n",
    "    num_cols=features_with_proportional_cost,\n",
    "    cate_cols=features_with_binary_cost,\n",
    "    ord_cols=ord_features,\n",
    "    feature_weights=feature_weights,\n",
    "    num_normalization=True,\n",
    "    feats_to_normalize = [\"capital-gain\",\"capital-loss\"]\n",
    ")\n",
    "params = ParameterProxy(featureChanges=comparators)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We continue with the rankings and selection of rules according to each of the proposed metrics."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Macro Viewpoint"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Equal Cost of Effectiveness (Macro)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, age = (26.0, 34.0], capital-loss = 0, education-num = 13, marital-status =  Never-married, relationship =  Not-in-family\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.20%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m80.95%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m71.43%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m20.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.20%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m65.74%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m10.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 10.0.\u001b[39m\n",
      "If \u001b[1mage = (34.0, 41.0], hours-per-week = FullTime, marital-status =  Never-married, relationship =  Not-in-family\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.38%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m50.00%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m22.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.43%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m50.39%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m12.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 10.\u001b[39m\n",
      "If \u001b[1mWorkclass =  Private, age = (34.0, 41.0], hours-per-week = FullTime, marital-status =  Never-married, relationship =  Not-in-family\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.03%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m50.00%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m50.00%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m50.00%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m22.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.13%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m50.00%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m14.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 8.\u001b[39m\n",
      "If \u001b[1meducation-num = 9, occupation =  Transport-moving, relationship =  Married\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.84%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m68.75%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m10.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.97%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m50.00%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m4.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 6.\u001b[39m\n",
      "If \u001b[1meducation-num = 9, marital-status =  Married-civ-spouse, native-country =  United-States, occupation =  Transport-moving\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.55%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m70.37%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m10.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.94%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m50.29%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m4.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 6.\u001b[39m\n",
      "If \u001b[1mage = (26.0, 34.0], education-num = 13, marital-status =  Never-married, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.26%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31meducation-num = 15\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m50.00%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m21.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.08%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m52.58%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m15.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 6.\u001b[39m\n",
      "If \u001b[1meducation-num = 13, marital-status =  Never-married, relationship =  Not-in-family, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.43%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 15\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m64.00%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m16.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m2.25%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m52.22%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m10.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 6.\u001b[39m\n",
      "If \u001b[1mcapital-loss = 0, marital-status =  Never-married, occupation =  Prof-specialty, relationship =  Not-in-family\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.18%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m55.26%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m14.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m3.31%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m60.07%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m10.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 4.0.\u001b[39m\n",
      "If \u001b[1mage = (26.0, 34.0], marital-status =  Never-married, occupation =  Prof-specialty, relationship =  Not-in-family\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.15%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m55.00%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m14.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.18%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m75.47%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m10.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 4.\u001b[39m\n",
      "If \u001b[1mWorkclass =  Private, age = (26.0, 34.0], hours-per-week = FullTime, marital-status =  Never-married, native-country =  United-States, relationship =  Not-in-family\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.89%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m60.61%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m24.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m2.22%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m52.00%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m20.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 4.\u001b[39m\n",
      "If \u001b[1mage = (26.0, 34.0], hours-per-week = FullTime, marital-status =  Never-married, relationship =  Not-in-family\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m3.56%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m50.00%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m24.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m2.87%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m51.35%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m20.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 4.\u001b[39m\n",
      "If \u001b[1mmarital-status =  Never-married, occupation =  Prof-specialty, relationship =  Not-in-family\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.24%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m56.41%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m14.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m3.46%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m61.86%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m10.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 4.\u001b[39m\n"
     ]
    }
   ],
   "source": [
    "top_rules, subgroup_costs = facts.select_rules_subset(\n",
    "    rules_by_if,\n",
    "    metric=\"min-above-thr\",\n",
    "    sort_strategy=\"generic-sorting-ignore-exists-subgroup-empty\",\n",
    "    top_count=50,\n",
    "    filter_sequence = [\n",
    "        \"remove-contained\",\n",
    "        \"remove-below-thr\",        \n",
    "        \"remove-fair-rules\",\n",
    "        \"keep-only-min-change\"\n",
    "    ],\n",
    "    cor_threshold=0.5,\n",
    "    secondary_sorting_objectives=[\n",
    "        # \"min-group-cost\",\n",
    "        \"max-group-corr\"\n",
    "    ],\n",
    "    params=params\n",
    ")\n",
    "\n",
    "# cum_cors = facts.cum_corr_costs_all_minimal(top_rules, X_test, model, sensitive_attribute=\"race\", params=params)\n",
    "cum_cors = dict()\n",
    "\n",
    "pop_sizes = {sg: ((X_test[\"race\"] == sg) & (preds_Xtest == 0)).sum() for sg in X_test[\"race\"].unique()}\n",
    "print_recourse_report(\n",
    "    top_rules,\n",
    "    population_sizes=pop_sizes,\n",
    "    subgroup_costs=subgroup_costs,\n",
    "    aggregate_cors_costs=cum_cors,\n",
    "    show_subgroup_costs=True\n",
    ")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Equal Choice for Recourse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, hours-per-week = PartTime, marital-status =  Married-civ-spouse\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.32%\u001b[39m covered out of 1727\n",
      "\t\t\u001b[31mNo recourses for this subgroup!\u001b[39m\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.54%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m35.97%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = FullTime\u001b[39m\u001b[0m with effectiveness \u001b[32m26.62%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m38.13%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m44.60%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m\u001b[0m with effectiveness \u001b[32m25.18%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m\u001b[0m with effectiveness \u001b[32m38.13%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m20.86%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m45.32%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m33.81%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m\u001b[0m with effectiveness \u001b[32m34.53%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m\u001b[0m with effectiveness \u001b[32m20.14%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m21.58%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m28.78%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-13.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 13.\u001b[39m\n",
      "If \u001b[1mWorkclass =  Private, hours-per-week = PartTime, relationship =  Married\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.20%\u001b[39m covered out of 1727\n",
      "\t\t\u001b[31mNo recourses for this subgroup!\u001b[39m\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.44%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m37.69%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = FullTime\u001b[39m\u001b[0m with effectiveness \u001b[32m27.69%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m40.00%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m46.92%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m\u001b[0m with effectiveness \u001b[32m26.15%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m\u001b[0m with effectiveness \u001b[32m40.00%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m21.54%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m47.69%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m35.38%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m\u001b[0m with effectiveness \u001b[32m36.15%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m\u001b[0m with effectiveness \u001b[32m20.77%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m22.31%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-13.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 13.\u001b[39m\n",
      "If \u001b[1mage = (34.0, 41.0], hours-per-week = FullTime, occupation =  Adm-clerical\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.58%\u001b[39m covered out of 1727\n",
      "\t\t\u001b[31mNo recourses for this subgroup!\u001b[39m\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.34%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m28.93%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m26.45%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m26.45%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m21.49%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m27.27%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m21.49%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m28.93%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m27.27%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m28.93%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m27.27%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m21.49%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-11.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 11.\u001b[39m\n",
      "If \u001b[1mWorkclass =  Private, capital-gain = 0, hours-per-week = FullTime, marital-status =  Divorced, relationship =  Unmarried\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.35%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m95.12%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-2.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m2.15%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m37.11%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m24.23%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m42.27%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m53.09%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m23.71%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m47.42%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m55.67%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m34.02%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m34.54%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m20.62%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m29.90%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m93.81%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-13.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 11.\u001b[39m\n",
      "If \u001b[1mWorkclass =  Private, age = (34.0, 41.0], marital-status =  Divorced, native-country =  United-States, relationship =  Unmarried\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.38%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m25.00%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-1.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.34%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m33.88%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m23.97%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m27.27%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m31.40%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m47.11%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m41.32%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m38.84%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m20.66%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m58.68%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m51.24%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m23.97%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m24.79%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-12.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 11.\u001b[39m\n",
      "If \u001b[1mWorkclass =  Private, age = (34.0, 41.0], capital-gain = 0, marital-status =  Divorced, native-country =  United-States, relationship =  Unmarried\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.38%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m25.00%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-3.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.29%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m31.03%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m21.55%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m25.00%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m28.45%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m44.83%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m38.79%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m36.21%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m56.90%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m21.55%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m22.41%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m49.14%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-13.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 10.\u001b[39m\n",
      "If \u001b[1mage = (34.0, 41.0], hours-per-week = FullTime, occupation =  Craft-repair, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.20%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m38.10%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m38.10%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m38.10%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m38.10%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m38.10%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m38.10%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m38.10%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m38.10%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-8.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.71%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m46.75%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m44.16%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m44.16%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m42.21%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m21.43%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m45.45%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m21.43%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m21.43%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m42.21%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m21.43%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m22.08%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m20.13%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m46.75%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m46.75%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m44.81%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m21.43%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m44.81%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m42.21%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-18.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 10.\u001b[39m\n",
      "If \u001b[1mWorkclass =  Private, capital-gain = 0, hours-per-week = PartTime, relationship =  Married\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.15%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m\u001b[0m with effectiveness \u001b[32m90.00%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-2.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.31%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m32.20%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = FullTime\u001b[39m\u001b[0m with effectiveness \u001b[32m22.03%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m34.75%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m\u001b[0m with effectiveness \u001b[32m21.19%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m42.37%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m\u001b[0m with effectiveness \u001b[32m34.75%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m43.22%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m29.66%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m\u001b[0m with effectiveness \u001b[32m30.51%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m23.73%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m\u001b[0m with effectiveness \u001b[32m93.22%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-12.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 10.\u001b[39m\n",
      "If \u001b[1mWorkclass =  Private, marital-status =  Divorced, occupation =  Adm-clerical, relationship =  Unmarried\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.15%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m50.00%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m35.00%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m70.00%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m50.00%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-6.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.06%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m52.08%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m39.58%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m26.04%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m66.67%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m33.33%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m27.08%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Tech-support\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m39.58%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m40.62%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m23.96%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m55.21%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m46.88%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m76.04%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m40.62%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m66.67%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m39.58%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Protective-serv\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m23.96%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-16.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 10.\u001b[39m\n",
      "If \u001b[1mWorkclass =  Private, hours-per-week = FullTime, native-country =  United-States, occupation =  Machine-op-inspct\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m5.51%\u001b[39m covered out of 1727\n",
      "\t\t\u001b[31mNo recourses for this subgroup!\u001b[39m\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m4.11%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m28.84%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m21.56%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m30.46%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m32.08%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m28.03%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m33.15%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m30.73%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m28.84%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m28.03%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-9.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 9.\u001b[39m\n",
      "If \u001b[1mWorkclass =  Private, marital-status =  Married-civ-spouse, occupation =  Machine-op-inspct\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m3.04%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m28.30%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m39.62%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m28.30%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-3.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m3.59%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m33.02%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m22.22%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m51.23%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m20.37%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m20.37%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m25.31%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m35.80%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m27.78%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m59.26%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m25.31%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m51.23%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m22.53%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-12.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 9.\u001b[39m\n",
      "If \u001b[1mWorkclass =  Private, occupation =  Machine-op-inspct, relationship =  Married\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.98%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m28.85%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m40.38%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m28.85%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-3.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m3.56%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m33.33%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m22.43%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m51.71%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m20.56%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m20.56%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m25.55%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m36.14%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m28.04%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m59.81%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m25.55%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m51.71%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m22.74%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-12.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 9.\u001b[39m\n",
      "If \u001b[1mWorkclass =  Private, age = (34.0, 41.0], hours-per-week = FullTime, marital-status =  Married-civ-spouse\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.70%\u001b[39m covered out of 1727\n",
      "\t\t\u001b[31mNo recourses for this subgroup!\u001b[39m\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m2.86%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m24.81%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m29.46%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m39.92%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m22.09%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m36.43%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m22.09%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m24.81%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m42.64%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m36.43%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-9.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 9.\u001b[39m\n",
      "If \u001b[1mWorkclass =  Private, age = (34.0, 41.0], hours-per-week = FullTime, relationship =  Married\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.64%\u001b[39m covered out of 1727\n",
      "\t\t\u001b[31mNo recourses for this subgroup!\u001b[39m\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m2.84%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m24.61%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m29.30%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m39.84%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m21.88%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m36.33%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m21.88%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m24.61%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m42.58%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m36.33%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-9.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 9.\u001b[39m\n",
      "If \u001b[1mWorkclass =  Private, capital-loss = 0, hours-per-week = FullTime, marital-status =  Divorced, relationship =  Unmarried\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.41%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m23.81%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m23.81%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-2.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m2.10%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m35.45%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m23.81%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m40.74%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m51.85%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m23.28%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m46.03%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m54.50%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m33.86%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m34.39%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m20.11%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m30.16%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-11.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 9.\u001b[39m\n",
      "If \u001b[1mWorkclass =  Private, hours-per-week = FullTime, marital-status =  Divorced, native-country =  United-States, relationship =  Unmarried\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.29%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m25.00%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m25.00%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-2.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m2.10%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m39.68%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m25.93%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m44.97%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m55.03%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m25.40%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m49.74%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m57.14%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m36.51%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m37.04%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m22.22%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m32.28%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-11.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 9.\u001b[39m\n",
      "If \u001b[1mWorkclass =  Self-emp-not-inc, hours-per-week = FullTime\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.61%\u001b[39m covered out of 1727\n",
      "\t\t\u001b[31mNo recourses for this subgroup!\u001b[39m\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m2.31%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Private\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m20.67%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Private\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m23.08%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m28.85%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m25.96%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m29.33%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m20.19%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m\u001b[0m with effectiveness \u001b[32m20.19%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m34.62%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m20.67%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-9.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 9.\u001b[39m\n",
      "If \u001b[1mWorkclass =  Private, age = (34.0, 41.0], native-country =  United-States, occupation =  Machine-op-inspct\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.55%\u001b[39m covered out of 1727\n",
      "\t\t\u001b[31mNo recourses for this subgroup!\u001b[39m\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.19%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m50.47%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m29.91%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m29.91%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m29.91%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m23.36%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m29.91%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m52.34%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m52.34%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m29.91%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-9.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 9.\u001b[39m\n",
      "If \u001b[1mWorkclass =  Private, marital-status =  Never-married, native-country =  United-States, occupation =  Prof-specialty\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.38%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m20.83%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-1.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m2.85%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m25.68%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m20.23%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m33.07%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m21.79%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m24.12%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m26.07%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m39.69%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m21.40%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m20.23%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m33.07%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-10.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 9.\u001b[39m\n",
      "If \u001b[1mWorkclass =  Private, age = (34.0, 41.0], occupation =  Sales\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.26%\u001b[39m covered out of 1727\n",
      "\t\t\u001b[31mNo recourses for this subgroup!\u001b[39m\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.01%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m31.87%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m21.98%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m21.98%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m21.98%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m21.98%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m35.16%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m32.97%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m21.98%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m31.87%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-9.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 9.\u001b[39m\n",
      "If \u001b[1mWorkclass =  Private, hours-per-week = FullTime, marital-status =  Never-married, native-country =  United-States, relationship =  Not-in-family, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.93%\u001b[39m covered out of 1727\n",
      "\t\t\u001b[31mNo recourses for this subgroup!\u001b[39m\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m3.70%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m23.35%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m25.15%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m30.84%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m25.75%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m32.04%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m21.26%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m21.26%\u001b[39m.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m20.36%\u001b[39m.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m-8.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 8.\u001b[39m\n"
     ]
    }
   ],
   "source": [
    "top_rules, subgroup_costs = facts.select_rules_subset(\n",
    "    rules_by_if,\n",
    "    metric=\"num-above-thr\",\n",
    "    sort_strategy=\"generic-sorting-ignore-forall-subgroups-empty\",\n",
    "    top_count=50,\n",
    "    filter_sequence = [\n",
    "        \"remove-contained\",\n",
    "        \"remove-below-thr\",\n",
    "        # \"remove-fair-rules\"\n",
    "    ],\n",
    "    cor_threshold=0.2,\n",
    "    secondary_sorting_objectives=[\n",
    "        # \"min-group-cost\",\n",
    "        # \"max-group-corr\"\n",
    "    ],\n",
    "    params=params\n",
    ")\n",
    "\n",
    "# cum_cors = facts.cum_corr_costs_all_minimal(top_rules, X_test, model, sensitive_attribute=\"race\", params=params)\n",
    "cum_cors = dict()\n",
    "\n",
    "pop_sizes = {sg: ((X_test[\"race\"] == sg) & (preds_Xtest == 0)).sum() for sg in X_test[\"race\"].unique()}\n",
    "print_recourse_report(\n",
    "    top_rules,\n",
    "    population_sizes = pop_sizes,\n",
    "    subgroup_costs=subgroup_costs,\n",
    "    aggregate_cors_costs=cum_cors,\n",
    "    show_subgroup_costs=True\n",
    ")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Micro viewpoint"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We start by computing the cumulative effectiveness of the actions for each subgroup and each value of the protected attribute.\n",
    "\n",
    "**Caution!** This step takes time. Uncomment the following block if you wish to run."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|████████████████████████████████████████████████████████████████████████████| 16641/16641 [17:29<00:00, 15.86it/s]\n"
     ]
    }
   ],
   "source": [
    "# rules_with_cumulative = facts.cum_corr_costs_all(rules_by_if, X_test, model, sensitive_attribute=\"race\", params=params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Use this for loading rules from disk\n",
    "rules_with_cumulative = load_rules_by_if(precomputed_rules_with_cumulative_file)\n",
    "\n",
    "## Use this for saving rules on disk\n",
    "# save_rules_by_if(precomputed_rules_with_cumulative_file, rules_with_cumulative)\n",
    "\n",
    "# facts.update_costs_cumulative(rules_with_cumulative, params)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Equal (Conditional) Mean Recourse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, capital-loss = 0, education-num = 10, hours-per-week = FullTime, marital-status =  Never-married, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.35%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m2.44%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m2.44%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m2.44%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m2.44%\u001b[39m and counterfactual cost = 21.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m2.44%\u001b[39m and counterfactual cost = 22.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 12\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m2.44%\u001b[39m and counterfactual cost = 42.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m1.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.84%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 21.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 22.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 12\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m2.41%\u001b[39m and counterfactual cost = 42.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m42.00\u001b[39m\n",
      "\t\u001b[35mBias against  White due to Equal Effectiveness. Unfairness score = 41.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25484 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, capital-loss = 0, education-num = 10, hours-per-week = FullTime, native-country =  United-States, relationship =  Not-in-family, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.20%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 10.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m4.76%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m4.76%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 12\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m4.76%\u001b[39m and counterfactual cost = 51.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m11.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.10%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 10.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 12\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m1.01%\u001b[39m and counterfactual cost = 51.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m51.00\u001b[39m\n",
      "\t\u001b[35mBias against  White due to Equal Effectiveness. Unfairness score = 40.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25352 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1meducation-num = 9, hours-per-week = FullTime, relationship =  Unmarried\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m5.28%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 10.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m1.09%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m1.09%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 10\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m1.09%\u001b[39m and counterfactual cost = 30.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m1.09%\u001b[39m and counterfactual cost = 31.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m1.09%\u001b[39m and counterfactual cost = 32.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m1.09%\u001b[39m and counterfactual cost = 50.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m1.09%\u001b[39m and counterfactual cost = 51.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m11.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m2.11%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 10.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 10\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 30.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 31.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 32.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 50.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m2.63%\u001b[39m and counterfactual cost = 51.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m51.00\u001b[39m\n",
      "\t\u001b[35mBias against  White due to Equal Effectiveness. Unfairness score = 40.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26000 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-loss = 0, education-num = 10, relationship =  Unmarried\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m5.22%\u001b[39m covered out of 1727\n",
      "\t\tMake \u001b[1m\u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 10.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 30.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 12\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m2.20%\u001b[39m and counterfactual cost = 50.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m50.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m2.50%\u001b[39m covered out of 9027\n",
      "\t\tMake \u001b[1m\u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m2.67%\u001b[39m and counterfactual cost = 10.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m2.67%\u001b[39m and counterfactual cost = 30.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 12\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m2.67%\u001b[39m and counterfactual cost = 50.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m10.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White due to Equal Effectiveness. Unfairness score = 40.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26192 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_rules, subgroup_costs = facts.select_rules_subset_cumulative(\n",
    "    rules_with_cumulative,\n",
    "    metric=\"fairness-of-mean-recourse-conditional\",\n",
    "    sort_strategy=\"generic-sorting-ignore-exists-subgroup-empty\",\n",
    "    top_count=10,\n",
    "    filter_sequence = [\n",
    "        \"remove-contained\",\n",
    "        # \"remove-fair-rules\"\n",
    "    ],\n",
    "    params=params\n",
    ")\n",
    "\n",
    "pop_sizes = {sg: ((X_test[\"race\"] == sg) & (preds_Xtest == 0)).sum() for sg in X_test[\"race\"].unique()}\n",
    "print_recourse_report_cumulative(\n",
    "    top_rules,\n",
    "    population_sizes=pop_sizes,\n",
    "    subgroup_costs=subgroup_costs,\n",
    "    show_subgroup_costs=True,\n",
    "    show_then_costs=True,\n",
    "    show_cumulative_plots=True,\n",
    "    correctness_metric=False\n",
    ")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Equal Effectiveness"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (16.999, 26.0], capital-gain = 0, capital-loss = 0, marital-status =  Never-married, occupation =  Handlers-cleaners, relationship =  Own-child, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.03%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m11.76%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m35.29%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m58.82%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m76.47%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.76\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.24%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m1.80%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m1.80%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m5.41%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m5.41%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m9.01%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m20.72%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.21\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 0.557.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 27512 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (16.999, 26.0], capital-gain = 0, capital-loss = 0, education-num = 9, hours-per-week = FullTime, marital-status =  Never-married, relationship =  Own-child\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.48%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m63.41%\u001b[39m and counterfactual cost = 33.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.63\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.73%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m12.90%\u001b[39m and counterfactual cost = 33.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.13\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 0.505.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 22060 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (16.999, 26.0], capital-gain = 0, hours-per-week = MidTime, marital-status =  Never-married, relationship =  Own-child\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.45%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m41.67%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m54.17%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m54.17%\u001b[39m and counterfactual cost = 14.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m62.50%\u001b[39m and counterfactual cost = 14.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m62.50%\u001b[39m and counterfactual cost = 15.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m70.83%\u001b[39m and counterfactual cost = 15.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.71\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m2.31%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m5.31%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m13.04%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m13.04%\u001b[39m and counterfactual cost = 14.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m23.67%\u001b[39m and counterfactual cost = 14.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m23.67%\u001b[39m and counterfactual cost = 15.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m23.67%\u001b[39m and counterfactual cost = 15.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.24\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 0.472.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26856 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (16.999, 26.0], marital-status =  Never-married, occupation =  Adm-clerical, relationship =  Own-child, sex =  Female\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.00%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m60.61%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.61\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.50%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m14.07%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.14\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 0.465.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 22436 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (16.999, 26.0], capital-gain = 0, capital-loss = 0, hours-per-week = PartTime, marital-status =  Never-married, occupation =  Sales, relationship =  Own-child\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.09%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m11.11%\u001b[39m and counterfactual cost = 15.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m27.78%\u001b[39m and counterfactual cost = 15.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m55.56%\u001b[39m and counterfactual cost = 15.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m83.33%\u001b[39m and counterfactual cost = 15.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m83.33%\u001b[39m and counterfactual cost = 15.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m83.33%\u001b[39m and counterfactual cost = 16.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m83.33%\u001b[39m and counterfactual cost = 16.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m83.33%\u001b[39m and counterfactual cost = 16.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 16.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m1.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.23%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m1.82%\u001b[39m and counterfactual cost = 15.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m3.64%\u001b[39m and counterfactual cost = 15.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m3.64%\u001b[39m and counterfactual cost = 15.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m40.91%\u001b[39m and counterfactual cost = 15.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m40.91%\u001b[39m and counterfactual cost = 15.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m40.91%\u001b[39m and counterfactual cost = 16.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m40.91%\u001b[39m and counterfactual cost = 16.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m43.64%\u001b[39m and counterfactual cost = 16.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m53.64%\u001b[39m and counterfactual cost = 16.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.54\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 0.464.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26104 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, education-num = 9, hours-per-week = FullTime, native-country =  United-States, occupation =  Sales\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.39%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 10\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 21.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 21.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 22.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.19%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m28.97%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 10\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m28.97%\u001b[39m and counterfactual cost = 21.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m28.97%\u001b[39m and counterfactual cost = 21.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m42.99%\u001b[39m and counterfactual cost = 22.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.43\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White. Unfairness score = 0.43.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 24072 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (16.999, 26.0], capital-gain = 0, capital-loss = 0, marital-status =  Never-married, native-country =  United-States, occupation =  Sales, relationship =  Own-child\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.75%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m13.79%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m24.14%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m24.14%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m24.14%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m37.93%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m55.17%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.55\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m2.13%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m3.14%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m5.76%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m5.76%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m5.76%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m7.85%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m15.71%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.16\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 0.395.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 24700 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Self-emp-not-inc, age = (34.0, 41.0]\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.03%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Private\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Private\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Private\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.56%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.71%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m4.29%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m5.71%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m10.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Private\u001b[39m\u001b[0m with effectiveness \u001b[32m14.29%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m\u001b[0m with effectiveness \u001b[32m26.43%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Private\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Private\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m33.57%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m39.29%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.39\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White. Unfairness score = 0.393.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 29296 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (16.999, 26.0], capital-gain = 0, capital-loss = 0, marital-status =  Never-married, occupation =  Adm-clerical, relationship =  Own-child\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.30%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m7.89%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m15.79%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m21.05%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m34.21%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m55.26%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m68.42%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.68\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m2.13%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m2.09%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m4.71%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m7.85%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m8.90%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m13.61%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m29.32%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.29\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 0.391.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 27196 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_rules, subgroup_costs = facts.select_rules_subset_cumulative(\n",
    "    rules_with_cumulative,\n",
    "    metric=\"total-correctness\",\n",
    "    sort_strategy=\"generic-sorting-ignore-forall-subgroups-empty\",\n",
    "    top_count=50,\n",
    "    filter_sequence = [\n",
    "        \"remove-contained\",\n",
    "        # \"remove-fair-rules\",\n",
    "        # \"keep-only-min-change\"\n",
    "    ],\n",
    "    params=params\n",
    ")\n",
    "\n",
    "pop_sizes = {sg: ((X_test[\"race\"] == sg) & (preds_Xtest == 0)).sum() for sg in X_test[\"race\"].unique()}\n",
    "print_recourse_report_cumulative(\n",
    "    top_rules,\n",
    "    population_sizes=pop_sizes,\n",
    "    subgroup_costs=subgroup_costs,\n",
    "    show_subgroup_costs=True,\n",
    "    show_then_costs=True,\n",
    "    show_cumulative_plots=True,\n",
    "    correctness_metric= True\n",
    ")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Equal Cost of Effectiveness (micro)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, education-num = 13, hours-per-week = FullTime, relationship =  Not-in-family, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.15%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m10.53%\u001b[39m and counterfactual cost = 10.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m31.58%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m11.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.38%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m4.03%\u001b[39m and counterfactual cost = 10.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m13.71%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m13.71%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 14\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m13.71%\u001b[39m and counterfactual cost = 30.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 14\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m22.58%\u001b[39m and counterfactual cost = 31.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 14\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m22.58%\u001b[39m and counterfactual cost = 32.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 15\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m22.58%\u001b[39m and counterfactual cost = 50.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 15\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m29.84%\u001b[39m and counterfactual cost = 51.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 15\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m30.65%\u001b[39m and counterfactual cost = 52.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m52.00\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 41.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25956 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1meducation-num = 10, hours-per-week = FullTime, marital-status =  Never-married, relationship =  Not-in-family\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.06%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m26.47%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m38.24%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m12.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.79%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m8.70%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m18.63%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m18.63%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m18.63%\u001b[39m and counterfactual cost = 31.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m29.19%\u001b[39m and counterfactual cost = 32.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 12\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m29.19%\u001b[39m and counterfactual cost = 51.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 12\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m39.13%\u001b[39m and counterfactual cost = 52.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m52.00\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 40.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26220 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-loss = 0, education-num = 10, marital-status =  Divorced, relationship =  Unmarried\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.06%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m47.06%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m11.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.46%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m19.85%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m28.24%\u001b[39m and counterfactual cost = 31.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 12\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m46.56%\u001b[39m and counterfactual cost = 51.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m51.00\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 40.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 24984 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, education-num = 10, marital-status =  Divorced, relationship =  Unmarried\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.00%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m45.45%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m11.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.43%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m16.41%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m25.78%\u001b[39m and counterfactual cost = 31.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 12\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m44.53%\u001b[39m and counterfactual cost = 51.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m51.00\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 40.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25708 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1meducation-num = 10, marital-status =  Divorced, native-country =  United-States, relationship =  Unmarried\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.88%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m45.16%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m11.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.46%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m21.37%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m29.77%\u001b[39m and counterfactual cost = 31.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 12\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m47.33%\u001b[39m and counterfactual cost = 51.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m51.00\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 40.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 24064 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (26.0, 34.0], education-num = 13, relationship =  Not-in-family\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.88%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m3.23%\u001b[39m and counterfactual cost = 10.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m16.13%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m32.26%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m11.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.92%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m2.33%\u001b[39m and counterfactual cost = 10.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m9.30%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m15.70%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 14\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m15.70%\u001b[39m and counterfactual cost = 30.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 14\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m15.70%\u001b[39m and counterfactual cost = 31.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31meducation-num = 14\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m26.16%\u001b[39m and counterfactual cost = 31.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 15\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m30.23%\u001b[39m and counterfactual cost = 51.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m51.00\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 40.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26016 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, education-num = 13, marital-status =  Never-married, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.69%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m17.86%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m17.86%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m17.86%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m17.86%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m21.43%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m32.14%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m2.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m2.56%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m8.26%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m8.26%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m8.26%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m8.26%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m10.87%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m20.43%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 14\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m20.43%\u001b[39m and counterfactual cost = 21.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31meducation-num = 14\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m20.43%\u001b[39m and counterfactual cost = 22.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31meducation-num = 14\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m20.43%\u001b[39m and counterfactual cost = 22.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 15\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m24.35%\u001b[39m and counterfactual cost = 41.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31meducation-num = 15\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m24.35%\u001b[39m and counterfactual cost = 42.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31meducation-num = 15\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m35.22%\u001b[39m and counterfactual cost = 42.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m42.00\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 40.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26832 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1meducation-num = 10, occupation =  Craft-repair\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.63%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m7.41%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m18.52%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m22.22%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m22.22%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m25.93%\u001b[39m and counterfactual cost = 21.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 12\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m33.33%\u001b[39m and counterfactual cost = 41.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m41.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m3.05%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m1.09%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m9.12%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m20.80%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m43.43%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m1.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White. Unfairness score = 40.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 24632 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, education-num = 10, hours-per-week = FullTime, marital-status =  Never-married, relationship =  Not-in-family\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.39%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m21.74%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m39.13%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m12.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.53%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m8.03%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m17.52%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m19.71%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m19.71%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m19.71%\u001b[39m and counterfactual cost = 31.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m28.47%\u001b[39m and counterfactual cost = 32.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 12\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m28.47%\u001b[39m and counterfactual cost = 51.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 12\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m37.23%\u001b[39m and counterfactual cost = 52.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m52.00\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 40.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26488 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1meducation-num = 11, hours-per-week = FullTime, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.33%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m9.09%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 12\u001b[39m\u001b[0m with effectiveness \u001b[32m9.09%\u001b[39m and counterfactual cost = 20.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 12\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m27.27%\u001b[39m and counterfactual cost = 21.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 13\u001b[39m\u001b[0m with effectiveness \u001b[32m27.27%\u001b[39m and counterfactual cost = 40.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 13\u001b[39m, \u001b[31mhours-per-week = MidTime\u001b[39m\u001b[0m with effectiveness \u001b[32m27.27%\u001b[39m and counterfactual cost = 41.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 13\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m31.82%\u001b[39m and counterfactual cost = 41.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m41.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.43%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m30.47%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m1.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White. Unfairness score = 40.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 24404 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-loss = 0, education-num = 13, hours-per-week = FullTime, marital-status =  Never-married, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.27%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m14.29%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = MidTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m14.29%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m33.33%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m2.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.56%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m2.86%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = MidTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m2.86%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m7.86%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m7.86%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 14\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m7.86%\u001b[39m and counterfactual cost = 21.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 14\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m27.14%\u001b[39m and counterfactual cost = 22.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 14\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m28.57%\u001b[39m and counterfactual cost = 23.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 15\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m28.57%\u001b[39m and counterfactual cost = 41.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 15\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m37.86%\u001b[39m and counterfactual cost = 42.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m42.00\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 40.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26936 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, education-num = 13, marital-status =  Never-married, occupation =  Prof-specialty\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.03%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m29.41%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m29.41%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m29.41%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m29.41%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m29.41%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m29.41%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m35.29%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m2.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.20%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m9.26%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m9.26%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m9.26%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m9.26%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m9.26%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m9.26%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m15.74%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m27.78%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 14\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m27.78%\u001b[39m and counterfactual cost = 21.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31meducation-num = 14\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m27.78%\u001b[39m and counterfactual cost = 22.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 14\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m27.78%\u001b[39m and counterfactual cost = 22.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 15\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m28.70%\u001b[39m and counterfactual cost = 41.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31meducation-num = 15\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m28.70%\u001b[39m and counterfactual cost = 42.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31meducation-num = 15\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m47.22%\u001b[39m and counterfactual cost = 42.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m42.00\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 40.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 27880 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, education-num = 11, hours-per-week = FullTime, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.03%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m5.88%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 12\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m29.41%\u001b[39m and counterfactual cost = 21.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 13\u001b[39m\u001b[0m with effectiveness \u001b[32m29.41%\u001b[39m and counterfactual cost = 40.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31meducation-num = 13\u001b[39m\u001b[0m with effectiveness \u001b[32m29.41%\u001b[39m and counterfactual cost = 41.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 13\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m35.29%\u001b[39m and counterfactual cost = 41.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m41.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.10%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m34.34%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m1.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White. Unfairness score = 40.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26244 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, capital-gain = 0, capital-loss = 0, education-num = 10, relationship =  Married\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.54%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m\u001b[0m with effectiveness \u001b[32m30.95%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m1.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m4.76%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m\u001b[0m with effectiveness \u001b[32m17.33%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m\u001b[0m with effectiveness \u001b[32m18.50%\u001b[39m and counterfactual cost = 20.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 12\u001b[39m\u001b[0m with effectiveness \u001b[32m43.56%\u001b[39m and counterfactual cost = 40.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m40.00\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 39.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 24204 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, capital-gain = 0, capital-loss = 0, education-num = 10, marital-status =  Married-civ-spouse, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.00%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m\u001b[0m with effectiveness \u001b[32m33.33%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m1.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m4.19%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m\u001b[0m with effectiveness \u001b[32m18.09%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m\u001b[0m with effectiveness \u001b[32m19.41%\u001b[39m and counterfactual cost = 20.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 12\u001b[39m\u001b[0m with effectiveness \u001b[32m45.21%\u001b[39m and counterfactual cost = 40.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m40.00\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 39.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25148 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, capital-gain = 0, capital-loss = 0, education-num = 10, marital-status =  Divorced, relationship =  Unmarried\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.03%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m29.41%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m52.94%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m12.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.06%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m13.68%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m22.11%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m22.11%\u001b[39m and counterfactual cost = 31.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 12\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m44.21%\u001b[39m and counterfactual cost = 51.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m51.00\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 39.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 27356 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1meducation-num = 9, hours-per-week = FullTime, occupation =  Other-service, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.42%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m2.50%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m35.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m1.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.09%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m2.04%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m12.24%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m28.57%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 10\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m28.57%\u001b[39m and counterfactual cost = 21.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m28.57%\u001b[39m and counterfactual cost = 22.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m32.65%\u001b[39m and counterfactual cost = 22.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m22.00\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 21.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26540 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, age = (26.0, 34.0], education-num = 11\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.21%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m5.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m20.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 12\u001b[39m\u001b[0m with effectiveness \u001b[32m20.00%\u001b[39m and counterfactual cost = 21.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31meducation-num = 12\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 21.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 13\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 40.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 13\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 41.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31meducation-num = 13\u001b[39m\u001b[0m with effectiveness \u001b[32m35.00%\u001b[39m and counterfactual cost = 41.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m21.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.18%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m13.21%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m17.92%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 12\u001b[39m\u001b[0m with effectiveness \u001b[32m18.87%\u001b[39m and counterfactual cost = 21.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31meducation-num = 12\u001b[39m\u001b[0m with effectiveness \u001b[32m24.53%\u001b[39m and counterfactual cost = 21.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 13\u001b[39m\u001b[0m with effectiveness \u001b[32m24.53%\u001b[39m and counterfactual cost = 40.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31meducation-num = 13\u001b[39m\u001b[0m with effectiveness \u001b[32m24.53%\u001b[39m and counterfactual cost = 41.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 13\u001b[39m\u001b[0m with effectiveness \u001b[32m24.53%\u001b[39m and counterfactual cost = 41.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31meducation-num = 13\u001b[39m\u001b[0m with effectiveness \u001b[32m24.53%\u001b[39m and counterfactual cost = 42.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31meducation-num = 13\u001b[39m\u001b[0m with effectiveness \u001b[32m24.53%\u001b[39m and counterfactual cost = 42.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31meducation-num = 13\u001b[39m\u001b[0m with effectiveness \u001b[32m30.19%\u001b[39m and counterfactual cost = 42.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m42.00\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 21.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 28052 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, education-num = 9, hours-per-week = FullTime, relationship =  Married\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m5.81%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m14.58%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m14.58%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 10\u001b[39m\u001b[0m with effectiveness \u001b[32m14.58%\u001b[39m and counterfactual cost = 20.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m29.17%\u001b[39m and counterfactual cost = 21.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31meducation-num = 10\u001b[39m\u001b[0m with effectiveness \u001b[32m29.17%\u001b[39m and counterfactual cost = 21.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m29.17%\u001b[39m and counterfactual cost = 22.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m\u001b[0m with effectiveness \u001b[32m29.17%\u001b[39m and counterfactual cost = 40.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 11\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m45.83%\u001b[39m and counterfactual cost = 41.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m41.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m6.86%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m11.85%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 10\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 20.0.\n",
      "\t\tMake \u001b[1m\u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m28.41%\u001b[39m and counterfactual cost = 21.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31meducation-num = 10\u001b[39m\u001b[0m with effectiveness \u001b[32m30.19%\u001b[39m and counterfactual cost = 21.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m21.00\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White. Unfairness score = 20.0.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 27348 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_rules, subgroup_costs = facts.select_rules_subset_cumulative(\n",
    "    rules_with_cumulative,\n",
    "    metric=\"min-above-corr\",\n",
    "    sort_strategy=\"generic-sorting-ignore-exists-subgroup-empty\",\n",
    "    top_count=50,\n",
    "    filter_sequence = [\n",
    "        \"remove-contained\",\n",
    "        \"remove-fair-rules\",\n",
    "        \"keep-cheap-rules-above-thr-cor\",\n",
    "        # \"keep-only-min-change\",\n",
    "        \n",
    "    ],\n",
    "    cor_threshold = 0.3,\n",
    "    params=params\n",
    ")\n",
    "\n",
    "pop_sizes = {sg: ((X_test[\"race\"] == sg) & (preds_Xtest == 0)).sum() for sg in X_test[\"race\"].unique()}\n",
    "print_recourse_report_cumulative(\n",
    "    top_rules,\n",
    "    population_sizes=pop_sizes,\n",
    "    subgroup_costs=subgroup_costs,\n",
    "    show_subgroup_costs=True,\n",
    "    show_then_costs=True,\n",
    "    show_cumulative_plots=True,\n",
    "    correctness_metric=False\n",
    ")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Equal Effectiveness Within Budget"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, capital-loss = 0, education-num = 9, marital-status =  Married-civ-spouse, occupation =  Other-service\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.00%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m57.58%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.58\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.00%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m17.78%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.18\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 0.398.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26228 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Self-emp-not-inc, age = (34.0, 41.0]\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.03%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Private\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Private\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Private\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.56%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.71%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m4.29%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m5.71%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m10.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Private\u001b[39m\u001b[0m with effectiveness \u001b[32m14.29%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m\u001b[0m with effectiveness \u001b[32m26.43%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Private\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Private\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m30.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m33.57%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m39.29%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.39\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White. Unfairness score = 0.393.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 29296 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (26.0, 34.0], capital-loss = 0, education-num = 9, hours-per-week = FullTime, marital-status =  Married-civ-spouse, native-country =  United-States, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.45%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m20.83%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m62.50%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m62.50%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.62\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.67%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m14.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m22.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m23.33%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.23\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 0.392.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 23548 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (26.0, 34.0], capital-loss = 0, education-num = 9, hours-per-week = FullTime, native-country =  United-States, relationship =  Married, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.45%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m20.83%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m62.50%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m62.50%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.62\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.66%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m14.09%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m22.15%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m23.49%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.23\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 0.39.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 23536 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-loss = 0, education-num = 9, occupation =  Other-service, relationship =  Married\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.00%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m12.12%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m18.18%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m60.61%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.61\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.00%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m3.33%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m8.89%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m22.22%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.22\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 0.384.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 24644 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (26.0, 34.0], capital-gain = 0, education-num = 9, hours-per-week = FullTime, marital-status =  Married-civ-spouse, native-country =  United-States, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.39%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m60.87%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.61\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.63%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m22.60%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.23\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 0.383.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26428 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (26.0, 34.0], capital-gain = 0, education-num = 9, hours-per-week = FullTime, native-country =  United-States, relationship =  Married, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.39%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m60.87%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.61\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.62%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m22.76%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.23\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 0.381.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26376 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (41.0, 50.0], capital-loss = 0, education-num = 9, hours-per-week = FullTime, native-country =  United-States, relationship =  Married\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.15%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m52.63%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m52.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m52.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.53\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.77%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m12.58%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m12.58%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m15.72%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.16\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 0.369.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 24132 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (41.0, 50.0], capital-gain = 0, education-num = 9, hours-per-week = FullTime, marital-status =  Married-civ-spouse, native-country =  United-States\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.15%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m52.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.53\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.79%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m16.77%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.17\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 0.359.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26616 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, education-num = 9, occupation =  Other-service, relationship =  Married\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.00%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m18.18%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m60.61%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.61\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.02%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m10.87%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m25.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.25\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 0.356.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 24016 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, age = (34.0, 41.0], capital-loss = 0, native-country =  United-States, occupation =  Machine-op-inspct\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.45%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m8.33%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m16.67%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m16.67%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m16.67%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m16.67%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.17\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.14%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m4.90%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m9.80%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m22.55%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m28.43%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m28.43%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m28.43%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m28.43%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m28.43%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m28.43%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m28.43%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m28.43%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m51.96%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m51.96%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m51.96%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m51.96%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.52\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White. Unfairness score = 0.353.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26328 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (34.0, 41.0], capital-loss = 0, native-country =  United-States, occupation =  Machine-op-inspct\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.45%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m8.33%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m8.33%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m16.67%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.17\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.20%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m5.56%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m7.41%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m11.11%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m24.07%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m24.07%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m29.63%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m29.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m29.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m29.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m29.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m29.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m29.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m29.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m29.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m29.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m29.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m51.85%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.52\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White. Unfairness score = 0.352.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25344 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, age = (34.0, 41.0], occupation =  Sales\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.21%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.01%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m2.20%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m15.38%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m15.38%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m21.98%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m21.98%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m21.98%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m21.98%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m21.98%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m21.98%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m21.98%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m21.98%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m21.98%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m31.87%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m31.87%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m31.87%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m32.97%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m35.16%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.35\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White. Unfairness score = 0.352.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 28592 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, capital-gain = 0, hours-per-week = OverTime, occupation =  Craft-repair\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.09%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = FullTime\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m5.56%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m5.56%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m11.11%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m11.11%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m11.11%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m11.11%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m11.11%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m11.11%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m11.11%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m11.11%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m11.11%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m16.67%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m16.67%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m16.67%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.17\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m2.70%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = FullTime\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m18.60%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m34.30%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m38.43%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m38.43%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m38.43%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m38.43%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m38.43%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m38.43%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m38.43%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m38.43%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m39.67%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m50.41%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mhours-per-week = FullTime\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m50.41%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m50.41%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.50\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White. Unfairness score = 0.337.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26316 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (34.0, 41.0], capital-gain = 0, native-country =  United-States, occupation =  Sales\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.09%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.00\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.08%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m2.06%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m15.46%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m15.46%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m22.68%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m22.68%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m22.68%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m22.68%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m22.68%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m22.68%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m22.68%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (41.0, 50.0]\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m32.99%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.33\u001b[39m\n",
      "\t\u001b[35mBias against  Non-White. Unfairness score = 0.33.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26192 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, capital-loss = 0, hours-per-week = FullTime, marital-status =  Married-civ-spouse, occupation =  Transport-moving\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.94%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m12.50%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m28.12%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m43.75%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m43.75%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m53.12%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = MidTime\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m53.12%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m53.12%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m53.12%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m59.38%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m87.50%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m87.50%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m87.50%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m87.50%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.88\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.43%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m2.34%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m3.91%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m10.94%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m10.94%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m26.56%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = MidTime\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m26.56%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m26.56%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m26.56%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m46.88%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m53.91%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m53.91%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m53.91%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m54.69%\u001b[39m and counterfactual cost = 3.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.55\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 0.328.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26772 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (41.0, 50.0], capital-loss = 0, education-num = 9, hours-per-week = FullTime, marital-status =  Married-civ-spouse, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m1.27%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m47.62%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m47.62%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m47.62%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.48\u001b[39m\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.73%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m13.55%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (50.0, 90.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m\u001b[0m with effectiveness \u001b[32m13.55%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mhours-per-week = BrainDrain\u001b[39m\u001b[0m with effectiveness \u001b[32m14.84%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\t\u001b[1mAggregate cost\u001b[0m of the above recourses = \u001b[35m0.15\u001b[39m\n",
      "\t\u001b[35mBias against  White. Unfairness score = 0.328.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 24120 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_rules, subgroup_costs = facts.select_rules_subset_cumulative(\n",
    "    rules_with_cumulative,\n",
    "    metric=\"max-upto-cost\",\n",
    "    sort_strategy=\"generic-sorting-ignore-exists-subgroup-empty\",\n",
    "    top_count=50,\n",
    "    filter_sequence = [\n",
    "        \"remove-contained\",\n",
    "        \"remove-fair-rules\",\n",
    "        \"remove-above-thr-cost\"\n",
    "        #\"remove-below-thr\",\n",
    "        #\"keep-only-min-change\",\n",
    "        \n",
    "    ],\n",
    "    cost_threshold = 10,\n",
    "    params=params\n",
    ")\n",
    "\n",
    "pop_sizes = {sg: ((X_test[\"race\"] == sg) & (preds_Xtest == 0)).sum() for sg in X_test[\"race\"].unique()}\n",
    "print_recourse_report_cumulative(\n",
    "    top_rules,\n",
    "    population_sizes=pop_sizes,\n",
    "    subgroup_costs=subgroup_costs,\n",
    "    show_subgroup_costs=True,\n",
    "    show_then_costs=True,\n",
    "    show_cumulative_plots=True,\n",
    "    correctness_metric = True\n",
    ")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fair Effectiveness-Cost Trade-Off"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, capital-loss = 0, marital-status =  Never-married, relationship =  Own-child\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m15.43%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m7.45%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m25.88%\u001b[39m and counterfactual cost = 11.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 4386\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m32.94%\u001b[39m and counterfactual cost = 11.04.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m45.10%\u001b[39m and counterfactual cost = 11.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m66.67%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m74.51%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.45.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m16.09%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m3.32%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m12.53%\u001b[39m and counterfactual cost = 11.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 4386\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m20.29%\u001b[39m and counterfactual cost = 11.04.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m24.38%\u001b[39m and counterfactual cost = 11.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m41.27%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m44.94%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.68%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.68%\u001b[39m and counterfactual cost = 11.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.68%\u001b[39m and counterfactual cost = 11.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.68%\u001b[39m and counterfactual cost = 11.45.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 4.46.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 28216 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, marital-status =  Never-married, relationship =  Own-child\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m15.73%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m8.08%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m26.54%\u001b[39m and counterfactual cost = 11.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 4386\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m33.46%\u001b[39m and counterfactual cost = 11.04.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m45.38%\u001b[39m and counterfactual cost = 11.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m66.92%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m74.62%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m16.49%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m3.78%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m13.18%\u001b[39m and counterfactual cost = 11.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 4386\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m20.95%\u001b[39m and counterfactual cost = 11.04.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m25.34%\u001b[39m and counterfactual cost = 11.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m42.03%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m45.68%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.76%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 4.41.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 27436 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, capital-loss = 0, marital-status =  Never-married, native-country =  United-States, relationship =  Own-child\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m13.01%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m7.44%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m27.44%\u001b[39m and counterfactual cost = 11.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 4386\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m35.35%\u001b[39m and counterfactual cost = 11.04.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m48.37%\u001b[39m and counterfactual cost = 11.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m66.51%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m75.81%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.45.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m15.35%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m3.34%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m12.77%\u001b[39m and counterfactual cost = 11.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 4386\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m20.39%\u001b[39m and counterfactual cost = 11.04.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m24.38%\u001b[39m and counterfactual cost = 11.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m41.36%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m45.14%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.73%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.73%\u001b[39m and counterfactual cost = 11.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.73%\u001b[39m and counterfactual cost = 11.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.73%\u001b[39m and counterfactual cost = 11.45.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 4.29.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 28172 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, marital-status =  Never-married, native-country =  United-States, relationship =  Own-child\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m13.25%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m8.22%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m27.85%\u001b[39m and counterfactual cost = 11.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 4386\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m35.62%\u001b[39m and counterfactual cost = 11.04.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m48.40%\u001b[39m and counterfactual cost = 11.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m66.67%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m75.80%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m15.75%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m3.82%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m13.44%\u001b[39m and counterfactual cost = 11.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 4386\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m21.07%\u001b[39m and counterfactual cost = 11.04.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m25.39%\u001b[39m and counterfactual cost = 11.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m42.15%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m45.90%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.82%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 4.22.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 27396 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, capital-gain = 0, capital-loss = 0, marital-status =  Never-married, relationship =  Own-child\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m13.07%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m6.94%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m63.89%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m73.15%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.45.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m13.98%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m2.79%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m39.20%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m42.87%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.49%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.49%\u001b[39m and counterfactual cost = 11.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.49%\u001b[39m and counterfactual cost = 11.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.49%\u001b[39m and counterfactual cost = 11.45.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.49%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.49%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.49%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.49%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.49%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 4.21.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26444 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, capital-gain = 0, marital-status =  Never-married, relationship =  Own-child\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m13.37%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m7.69%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m64.25%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m73.30%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m14.34%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m3.19%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m40.02%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m43.67%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.58%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.58%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.58%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.58%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.58%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.58%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 4.17.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25568 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, capital-gain = 0, capital-loss = 0, marital-status =  Never-married, native-country =  United-States, relationship =  Own-child\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m10.77%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m6.74%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m62.92%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m74.16%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.45.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m13.37%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m2.75%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m39.33%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m43.08%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.58%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.58%\u001b[39m and counterfactual cost = 11.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.58%\u001b[39m and counterfactual cost = 11.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.58%\u001b[39m and counterfactual cost = 11.45.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.58%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.58%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.58%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.58%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.58%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 3.96.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26412 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, capital-gain = 0, marital-status =  Never-married, native-country =  United-States, relationship =  Own-child\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m11.01%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m7.69%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m63.19%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m74.18%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m13.72%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m3.17%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m40.18%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m43.91%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.67%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.67%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.67%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.67%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.67%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m96.67%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 3.9.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25524 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, marital-status =  Never-married, occupation =  Other-service\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m8.11%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Transport-moving\u001b[39m\u001b[0m with effectiveness \u001b[32m0.75%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m1.49%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m1.49%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m1.49%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Protective-serv\u001b[39m\u001b[0m with effectiveness \u001b[32m1.49%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m2.99%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m2.99%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m3.73%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m59.70%\u001b[39m and counterfactual cost = 2.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 2.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 2.15.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m6.35%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Transport-moving\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m0.18%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Protective-serv\u001b[39m\u001b[0m with effectiveness \u001b[32m0.35%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m0.53%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m0.53%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m1.05%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m26.67%\u001b[39m and counterfactual cost = 2.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m88.77%\u001b[39m and counterfactual cost = 2.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m94.56%\u001b[39m and counterfactual cost = 2.15.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 3.52.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25500 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, native-country =  United-States\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m76.71%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m\u001b[0m with effectiveness \u001b[32m11.04%\u001b[39m and counterfactual cost = 0.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 4386\u001b[39m\u001b[0m with effectiveness \u001b[32m17.74%\u001b[39m and counterfactual cost = 0.04.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m\u001b[0m with effectiveness \u001b[32m22.00%\u001b[39m and counterfactual cost = 0.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m\u001b[0m with effectiveness \u001b[32m34.23%\u001b[39m and counterfactual cost = 0.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m\u001b[0m with effectiveness \u001b[32m36.91%\u001b[39m and counterfactual cost = 0.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m\u001b[0m with effectiveness \u001b[32m83.36%\u001b[39m and counterfactual cost = 0.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m89.26%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m\u001b[0m with effectiveness \u001b[32m20.14%\u001b[39m and counterfactual cost = 0.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 4386\u001b[39m\u001b[0m with effectiveness \u001b[32m27.47%\u001b[39m and counterfactual cost = 0.04.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m\u001b[0m with effectiveness \u001b[32m32.24%\u001b[39m and counterfactual cost = 0.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m\u001b[0m with effectiveness \u001b[32m43.88%\u001b[39m and counterfactual cost = 0.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m\u001b[0m with effectiveness \u001b[32m45.95%\u001b[39m and counterfactual cost = 0.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m\u001b[0m with effectiveness \u001b[32m80.47%\u001b[39m and counterfactual cost = 0.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 3.47.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26104 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, capital-loss = 0, marital-status =  Never-married, occupation =  Other-service\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m7.86%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m0.77%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m0.77%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m0.77%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Protective-serv\u001b[39m\u001b[0m with effectiveness \u001b[32m0.77%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m2.31%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m2.31%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m3.08%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m59.23%\u001b[39m and counterfactual cost = 2.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 2.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 2.15.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m6.24%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m0.18%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Protective-serv\u001b[39m\u001b[0m with effectiveness \u001b[32m0.36%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m0.54%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m0.54%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m1.07%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m26.43%\u001b[39m and counterfactual cost = 2.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m88.57%\u001b[39m and counterfactual cost = 2.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m94.46%\u001b[39m and counterfactual cost = 2.15.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 3.45.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25336 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, capital-loss = 0, native-country =  United-States\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m74.83%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m\u001b[0m with effectiveness \u001b[32m10.43%\u001b[39m and counterfactual cost = 0.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 4386\u001b[39m\u001b[0m with effectiveness \u001b[32m17.14%\u001b[39m and counterfactual cost = 0.04.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m\u001b[0m with effectiveness \u001b[32m21.42%\u001b[39m and counterfactual cost = 0.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m\u001b[0m with effectiveness \u001b[32m33.63%\u001b[39m and counterfactual cost = 0.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m\u001b[0m with effectiveness \u001b[32m36.14%\u001b[39m and counterfactual cost = 0.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m\u001b[0m with effectiveness \u001b[32m83.10%\u001b[39m and counterfactual cost = 0.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m\u001b[0m with effectiveness \u001b[32m83.10%\u001b[39m and counterfactual cost = 0.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m\u001b[0m with effectiveness \u001b[32m83.10%\u001b[39m and counterfactual cost = 0.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m\u001b[0m with effectiveness \u001b[32m83.10%\u001b[39m and counterfactual cost = 0.45.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m86.52%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m\u001b[0m with effectiveness \u001b[32m19.74%\u001b[39m and counterfactual cost = 0.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 4386\u001b[39m\u001b[0m with effectiveness \u001b[32m26.88%\u001b[39m and counterfactual cost = 0.04.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m\u001b[0m with effectiveness \u001b[32m31.53%\u001b[39m and counterfactual cost = 0.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m\u001b[0m with effectiveness \u001b[32m43.11%\u001b[39m and counterfactual cost = 0.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m\u001b[0m with effectiveness \u001b[32m45.18%\u001b[39m and counterfactual cost = 0.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m\u001b[0m with effectiveness \u001b[32m80.04%\u001b[39m and counterfactual cost = 0.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m\u001b[0m with effectiveness \u001b[32m80.04%\u001b[39m and counterfactual cost = 0.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m\u001b[0m with effectiveness \u001b[32m80.04%\u001b[39m and counterfactual cost = 0.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m\u001b[0m with effectiveness \u001b[32m80.04%\u001b[39m and counterfactual cost = 0.45.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 3.38.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26880 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (16.999, 26.0], capital-gain = 0, capital-loss = 0, relationship =  Own-child\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m10.89%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m1.11%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m57.78%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.15.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m13.24%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.08%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.17%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m32.38%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.14%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 3.25.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 24736 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (16.999, 26.0], capital-gain = 0, relationship =  Own-child\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m11.07%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m1.09%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m57.92%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.15.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m13.57%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.25%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m0.41%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m33.17%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.21%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 3.2.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 24744 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, marital-status =  Never-married, native-country =  United-States, occupation =  Other-service\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m6.84%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Transport-moving\u001b[39m\u001b[0m with effectiveness \u001b[32m0.88%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m1.77%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m1.77%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m1.77%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Protective-serv\u001b[39m\u001b[0m with effectiveness \u001b[32m1.77%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m3.54%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m3.54%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m3.54%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m59.29%\u001b[39m and counterfactual cost = 2.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 2.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 2.15.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m5.75%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Transport-moving\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m0.19%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Protective-serv\u001b[39m\u001b[0m with effectiveness \u001b[32m0.39%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m0.58%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m0.58%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m0.97%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m27.33%\u001b[39m and counterfactual cost = 2.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m88.95%\u001b[39m and counterfactual cost = 2.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m94.96%\u001b[39m and counterfactual cost = 2.15.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 3.15.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25372 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m96.37%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m\u001b[0m with effectiveness \u001b[32m11.36%\u001b[39m and counterfactual cost = 0.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 4386\u001b[39m\u001b[0m with effectiveness \u001b[32m18.08%\u001b[39m and counterfactual cost = 0.04.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m\u001b[0m with effectiveness \u001b[32m22.91%\u001b[39m and counterfactual cost = 0.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m\u001b[0m with effectiveness \u001b[32m34.97%\u001b[39m and counterfactual cost = 0.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m\u001b[0m with effectiveness \u001b[32m37.79%\u001b[39m and counterfactual cost = 0.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m\u001b[0m with effectiveness \u001b[32m82.74%\u001b[39m and counterfactual cost = 0.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m96.58%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m\u001b[0m with effectiveness \u001b[32m19.37%\u001b[39m and counterfactual cost = 0.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 4386\u001b[39m\u001b[0m with effectiveness \u001b[32m26.46%\u001b[39m and counterfactual cost = 0.04.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m\u001b[0m with effectiveness \u001b[32m31.08%\u001b[39m and counterfactual cost = 0.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m\u001b[0m with effectiveness \u001b[32m42.51%\u001b[39m and counterfactual cost = 0.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m\u001b[0m with effectiveness \u001b[32m44.54%\u001b[39m and counterfactual cost = 0.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m\u001b[0m with effectiveness \u001b[32m79.48%\u001b[39m and counterfactual cost = 0.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 3.15.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26008 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, capital-loss = 0\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m94.13%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m\u001b[0m with effectiveness \u001b[32m10.80%\u001b[39m and counterfactual cost = 0.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 4386\u001b[39m\u001b[0m with effectiveness \u001b[32m17.48%\u001b[39m and counterfactual cost = 0.04.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m\u001b[0m with effectiveness \u001b[32m22.30%\u001b[39m and counterfactual cost = 0.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m\u001b[0m with effectiveness \u001b[32m34.38%\u001b[39m and counterfactual cost = 0.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m\u001b[0m with effectiveness \u001b[32m37.08%\u001b[39m and counterfactual cost = 0.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m\u001b[0m with effectiveness \u001b[32m82.46%\u001b[39m and counterfactual cost = 0.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m\u001b[0m with effectiveness \u001b[32m82.46%\u001b[39m and counterfactual cost = 0.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m\u001b[0m with effectiveness \u001b[32m82.46%\u001b[39m and counterfactual cost = 0.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m\u001b[0m with effectiveness \u001b[32m82.46%\u001b[39m and counterfactual cost = 0.45.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m93.72%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m\u001b[0m with effectiveness \u001b[32m18.97%\u001b[39m and counterfactual cost = 0.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 4386\u001b[39m\u001b[0m with effectiveness \u001b[32m25.89%\u001b[39m and counterfactual cost = 0.04.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m\u001b[0m with effectiveness \u001b[32m30.39%\u001b[39m and counterfactual cost = 0.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m\u001b[0m with effectiveness \u001b[32m41.76%\u001b[39m and counterfactual cost = 0.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m\u001b[0m with effectiveness \u001b[32m43.79%\u001b[39m and counterfactual cost = 0.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m\u001b[0m with effectiveness \u001b[32m79.04%\u001b[39m and counterfactual cost = 0.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m\u001b[0m with effectiveness \u001b[32m79.04%\u001b[39m and counterfactual cost = 0.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m\u001b[0m with effectiveness \u001b[32m79.04%\u001b[39m and counterfactual cost = 0.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m\u001b[0m with effectiveness \u001b[32m79.04%\u001b[39m and counterfactual cost = 0.45.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 3.12.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26856 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-loss = 0, native-country =  United-States\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m77.80%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m\u001b[0m with effectiveness \u001b[32m14.31%\u001b[39m and counterfactual cost = 0.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m\u001b[0m with effectiveness \u001b[32m14.46%\u001b[39m and counterfactual cost = 0.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m\u001b[0m with effectiveness \u001b[32m14.93%\u001b[39m and counterfactual cost = 0.45.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m89.71%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m\u001b[0m with effectiveness \u001b[32m22.89%\u001b[39m and counterfactual cost = 0.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m\u001b[0m with effectiveness \u001b[32m23.20%\u001b[39m and counterfactual cost = 0.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m\u001b[0m with effectiveness \u001b[32m24.07%\u001b[39m and counterfactual cost = 0.45.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 3.12.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 24716 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, capital-loss = 0, marital-status =  Never-married, native-country =  United-States, occupation =  Other-service\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m6.59%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m0.92%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m0.92%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m0.92%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Protective-serv\u001b[39m\u001b[0m with effectiveness \u001b[32m0.92%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m2.75%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m2.75%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m2.75%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m58.72%\u001b[39m and counterfactual cost = 2.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 2.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 2.15.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m5.64%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m0.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m0.20%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Protective-serv\u001b[39m\u001b[0m with effectiveness \u001b[32m0.40%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m0.59%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m0.59%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m0.99%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m27.08%\u001b[39m and counterfactual cost = 2.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m88.74%\u001b[39m and counterfactual cost = 2.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m94.86%\u001b[39m and counterfactual cost = 2.15.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 3.07.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25304 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, capital-loss = 0, occupation =  Other-service\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m18.21%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m1.99%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m2.66%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m3.99%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Protective-serv\u001b[39m\u001b[0m with effectiveness \u001b[32m5.98%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m8.31%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m8.64%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m10.30%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m41.53%\u001b[39m and counterfactual cost = 1.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m90.03%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m91.36%\u001b[39m and counterfactual cost = 1.15.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m11.98%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m0.93%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m1.12%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m1.86%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Protective-serv\u001b[39m\u001b[0m with effectiveness \u001b[32m2.23%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m2.70%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m2.79%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m4.93%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m25.21%\u001b[39m and counterfactual cost = 1.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m70.70%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m75.16%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 3.03.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25792 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, native-country =  United-States, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m36.54%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m\u001b[0m with effectiveness \u001b[32m17.88%\u001b[39m and counterfactual cost = 0.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m\u001b[0m with effectiveness \u001b[32m30.13%\u001b[39m and counterfactual cost = 0.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m\u001b[0m with effectiveness \u001b[32m42.88%\u001b[39m and counterfactual cost = 0.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m\u001b[0m with effectiveness \u001b[32m44.54%\u001b[39m and counterfactual cost = 0.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m\u001b[0m with effectiveness \u001b[32m83.28%\u001b[39m and counterfactual cost = 0.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m56.01%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m\u001b[0m with effectiveness \u001b[32m28.20%\u001b[39m and counterfactual cost = 0.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m\u001b[0m with effectiveness \u001b[32m42.84%\u001b[39m and counterfactual cost = 0.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m\u001b[0m with effectiveness \u001b[32m54.24%\u001b[39m and counterfactual cost = 0.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m\u001b[0m with effectiveness \u001b[32m56.46%\u001b[39m and counterfactual cost = 0.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m\u001b[0m with effectiveness \u001b[32m84.39%\u001b[39m and counterfactual cost = 0.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 3.03.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25148 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-loss = 0\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m97.76%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m\u001b[0m with effectiveness \u001b[32m14.79%\u001b[39m and counterfactual cost = 0.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m\u001b[0m with effectiveness \u001b[32m14.91%\u001b[39m and counterfactual cost = 0.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m\u001b[0m with effectiveness \u001b[32m15.28%\u001b[39m and counterfactual cost = 0.45.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m97.14%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m\u001b[0m with effectiveness \u001b[32m22.03%\u001b[39m and counterfactual cost = 0.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m\u001b[0m with effectiveness \u001b[32m22.32%\u001b[39m and counterfactual cost = 0.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m\u001b[0m with effectiveness \u001b[32m23.18%\u001b[39m and counterfactual cost = 0.45.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.98.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 23084 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, occupation =  Other-service\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m18.57%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Transport-moving\u001b[39m\u001b[0m with effectiveness \u001b[32m0.98%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m2.28%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m2.93%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m4.23%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Protective-serv\u001b[39m\u001b[0m with effectiveness \u001b[32m6.19%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m8.47%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m8.79%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m10.42%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m42.02%\u001b[39m and counterfactual cost = 1.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m89.90%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m91.53%\u001b[39m and counterfactual cost = 1.15.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m12.31%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Transport-moving\u001b[39m\u001b[0m with effectiveness \u001b[32m1.18%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m1.54%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m1.81%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m2.53%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Protective-serv\u001b[39m\u001b[0m with effectiveness \u001b[32m2.90%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m3.35%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m3.44%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m5.70%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m26.15%\u001b[39m and counterfactual cost = 1.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m71.13%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m75.57%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.97.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25856 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (16.999, 26.0], capital-gain = 0, capital-loss = 0, education-num = 9, hours-per-week = FullTime, marital-status =  Never-married, relationship =  Own-child\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.48%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m63.41%\u001b[39m and counterfactual cost = 33.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.73%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m12.90%\u001b[39m and counterfactual cost = 33.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.94.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 22060 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, capital-loss = 0, native-country =  United-States, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m35.51%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m\u001b[0m with effectiveness \u001b[32m17.21%\u001b[39m and counterfactual cost = 0.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m\u001b[0m with effectiveness \u001b[32m29.81%\u001b[39m and counterfactual cost = 0.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m\u001b[0m with effectiveness \u001b[32m42.42%\u001b[39m and counterfactual cost = 0.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m\u001b[0m with effectiveness \u001b[32m43.95%\u001b[39m and counterfactual cost = 0.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m\u001b[0m with effectiveness \u001b[32m83.13%\u001b[39m and counterfactual cost = 0.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m\u001b[0m with effectiveness \u001b[32m83.13%\u001b[39m and counterfactual cost = 0.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m\u001b[0m with effectiveness \u001b[32m83.13%\u001b[39m and counterfactual cost = 0.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m\u001b[0m with effectiveness \u001b[32m83.13%\u001b[39m and counterfactual cost = 0.45.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m54.35%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m\u001b[0m with effectiveness \u001b[32m27.83%\u001b[39m and counterfactual cost = 0.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m\u001b[0m with effectiveness \u001b[32m42.24%\u001b[39m and counterfactual cost = 0.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m\u001b[0m with effectiveness \u001b[32m53.66%\u001b[39m and counterfactual cost = 0.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m\u001b[0m with effectiveness \u001b[32m55.91%\u001b[39m and counterfactual cost = 0.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m\u001b[0m with effectiveness \u001b[32m84.05%\u001b[39m and counterfactual cost = 0.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m\u001b[0m with effectiveness \u001b[32m84.05%\u001b[39m and counterfactual cost = 0.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m\u001b[0m with effectiveness \u001b[32m84.05%\u001b[39m and counterfactual cost = 0.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m\u001b[0m with effectiveness \u001b[32m84.05%\u001b[39m and counterfactual cost = 0.45.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.92.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25892 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (16.999, 26.0], capital-gain = 0, education-num = 9, hours-per-week = FullTime, marital-status =  Never-married, relationship =  Own-child\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.48%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m63.41%\u001b[39m and counterfactual cost = 33.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.74%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m13.46%\u001b[39m and counterfactual cost = 33.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.91.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 22048 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (16.999, 26.0], capital-loss = 0, education-num = 9, hours-per-week = FullTime, marital-status =  Never-married, relationship =  Own-child\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.48%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m39.02%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 10\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m39.02%\u001b[39m and counterfactual cost = 32.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m63.41%\u001b[39m and counterfactual cost = 33.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.77%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m5.66%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 10\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m5.66%\u001b[39m and counterfactual cost = 32.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m14.47%\u001b[39m and counterfactual cost = 33.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.86.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 24248 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, capital-gain = 0, capital-loss = 0, marital-status =  Never-married, relationship =  Own-child, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m7.26%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m4.17%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m61.67%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m73.33%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.45.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m7.93%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m3.09%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m40.45%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m46.07%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.19%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.19%\u001b[39m and counterfactual cost = 11.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.19%\u001b[39m and counterfactual cost = 11.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.19%\u001b[39m and counterfactual cost = 11.45.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.19%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.19%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.19%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.19%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.19%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.83.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26464 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (16.999, 26.0], education-num = 9, hours-per-week = FullTime, marital-status =  Never-married, relationship =  Own-child\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.48%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m39.02%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 10\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m39.02%\u001b[39m and counterfactual cost = 32.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m63.41%\u001b[39m and counterfactual cost = 33.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.78%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m6.25%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 10\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m6.25%\u001b[39m and counterfactual cost = 32.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m15.00%\u001b[39m and counterfactual cost = 33.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.83.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 24220 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, capital-gain = 0, native-country =  United-States\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m57.89%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m\u001b[0m with effectiveness \u001b[32m30.09%\u001b[39m and counterfactual cost = 0.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m\u001b[0m with effectiveness \u001b[32m32.71%\u001b[39m and counterfactual cost = 0.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m\u001b[0m with effectiveness \u001b[32m80.67%\u001b[39m and counterfactual cost = 0.15.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m80.67%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m\u001b[0m with effectiveness \u001b[32m80.67%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m80.67%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m\u001b[0m with effectiveness \u001b[32m80.67%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m80.67%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m68.69%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m\u001b[0m with effectiveness \u001b[32m39.62%\u001b[39m and counterfactual cost = 0.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m\u001b[0m with effectiveness \u001b[32m41.70%\u001b[39m and counterfactual cost = 0.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m\u001b[0m with effectiveness \u001b[32m77.55%\u001b[39m and counterfactual cost = 0.15.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m77.55%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m\u001b[0m with effectiveness \u001b[32m77.55%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m77.55%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m\u001b[0m with effectiveness \u001b[32m77.55%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m77.55%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.81.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26452 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, capital-loss = 0, marital-status =  Never-married, relationship =  Own-child, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m8.47%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m5.71%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m24.29%\u001b[39m and counterfactual cost = 11.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m43.57%\u001b[39m and counterfactual cost = 11.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m62.86%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m72.86%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.45.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m9.22%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m3.62%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m13.04%\u001b[39m and counterfactual cost = 11.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m26.45%\u001b[39m and counterfactual cost = 11.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m42.51%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m47.83%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.22%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.22%\u001b[39m and counterfactual cost = 11.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.22%\u001b[39m and counterfactual cost = 11.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.22%\u001b[39m and counterfactual cost = 11.45.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.81.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 28084 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, capital-gain = 0, marital-status =  Never-married, relationship =  Own-child, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m7.50%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m5.65%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m62.10%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m73.39%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m8.11%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m3.43%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m41.21%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m46.84%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.25%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.25%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.25%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.25%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.25%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.25%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.8.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25704 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, marital-status =  Never-married, relationship =  Own-child, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m8.71%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m6.94%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m25.00%\u001b[39m and counterfactual cost = 11.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m43.75%\u001b[39m and counterfactual cost = 11.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m63.19%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m72.92%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m9.45%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m4.13%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m13.68%\u001b[39m and counterfactual cost = 11.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m27.48%\u001b[39m and counterfactual cost = 11.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m43.28%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m48.58%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.29%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.76.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 27160 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, capital-loss = 0, marital-status =  Never-married, native-country =  United-States, relationship =  Own-child, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m7.08%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m6.84%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m26.50%\u001b[39m and counterfactual cost = 11.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m47.01%\u001b[39m and counterfactual cost = 11.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m63.25%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m75.21%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.45.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m8.77%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m3.68%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m13.60%\u001b[39m and counterfactual cost = 11.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m26.94%\u001b[39m and counterfactual cost = 11.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m43.07%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m48.67%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.33%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.33%\u001b[39m and counterfactual cost = 11.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.33%\u001b[39m and counterfactual cost = 11.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.33%\u001b[39m and counterfactual cost = 11.45.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.75.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 27876 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, capital-gain = 0, capital-loss = 0, native-country =  United-States\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m56.38%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m\u001b[0m with effectiveness \u001b[32m29.40%\u001b[39m and counterfactual cost = 0.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m\u001b[0m with effectiveness \u001b[32m31.87%\u001b[39m and counterfactual cost = 0.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m\u001b[0m with effectiveness \u001b[32m80.36%\u001b[39m and counterfactual cost = 0.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m\u001b[0m with effectiveness \u001b[32m80.36%\u001b[39m and counterfactual cost = 0.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m\u001b[0m with effectiveness \u001b[32m80.36%\u001b[39m and counterfactual cost = 0.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m\u001b[0m with effectiveness \u001b[32m80.36%\u001b[39m and counterfactual cost = 0.45.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m80.36%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m\u001b[0m with effectiveness \u001b[32m80.36%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m80.36%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m\u001b[0m with effectiveness \u001b[32m80.36%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m80.36%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m66.61%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m\u001b[0m with effectiveness \u001b[32m38.83%\u001b[39m and counterfactual cost = 0.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m\u001b[0m with effectiveness \u001b[32m40.92%\u001b[39m and counterfactual cost = 0.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m\u001b[0m with effectiveness \u001b[32m77.09%\u001b[39m and counterfactual cost = 0.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m\u001b[0m with effectiveness \u001b[32m77.09%\u001b[39m and counterfactual cost = 0.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m\u001b[0m with effectiveness \u001b[32m77.09%\u001b[39m and counterfactual cost = 0.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m\u001b[0m with effectiveness \u001b[32m77.09%\u001b[39m and counterfactual cost = 0.45.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m77.09%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m\u001b[0m with effectiveness \u001b[32m77.09%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m77.09%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m\u001b[0m with effectiveness \u001b[32m77.09%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m\u001b[0m with effectiveness \u001b[32m77.09%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.74.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 27336 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, capital-gain = 0, capital-loss = 0, marital-status =  Never-married, native-country =  United-States, relationship =  Own-child, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m5.99%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m5.05%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m61.62%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m75.76%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.45.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m7.54%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m3.10%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m41.06%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m46.97%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.34%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.34%\u001b[39m and counterfactual cost = 11.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.34%\u001b[39m and counterfactual cost = 11.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.34%\u001b[39m and counterfactual cost = 11.45.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.34%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.34%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.34%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.34%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.34%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.74.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26560 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, capital-loss = 0, native-country =  United-States, occupation =  Other-service\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m13.91%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m1.30%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m1.74%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m3.04%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Protective-serv\u001b[39m\u001b[0m with effectiveness \u001b[32m4.35%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m6.96%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m7.39%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m9.13%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m37.39%\u001b[39m and counterfactual cost = 1.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m90.00%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m91.30%\u001b[39m and counterfactual cost = 1.15.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m10.50%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m0.95%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m1.17%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m1.91%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Protective-serv\u001b[39m\u001b[0m with effectiveness \u001b[32m2.33%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m2.76%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m2.86%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m5.09%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m25.03%\u001b[39m and counterfactual cost = 1.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m70.31%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m74.66%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.74.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25720 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (16.999, 26.0], capital-gain = 0, capital-loss = 0, marital-status =  Never-married\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m20.39%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m1.19%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m3.26%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m58.16%\u001b[39m and counterfactual cost = 2.07.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 2.15.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m21.30%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m0.10%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m1.88%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m42.47%\u001b[39m and counterfactual cost = 2.07.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m96.03%\u001b[39m and counterfactual cost = 2.15.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.72.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25136 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, capital-gain = 0, marital-status =  Never-married, native-country =  United-States, relationship =  Own-child, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m6.23%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m6.80%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m62.14%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m75.73%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m7.72%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m3.46%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m41.85%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m47.76%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.40%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.40%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.40%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.40%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.40%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.40%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.71.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25480 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, age = (16.999, 26.0], capital-gain = 0, education-num = 9, hours-per-week = FullTime, marital-status =  Never-married, relationship =  Own-child\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.24%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m62.16%\u001b[39m and counterfactual cost = 33.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.54%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m13.04%\u001b[39m and counterfactual cost = 33.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.71.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 22112 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, marital-status =  Never-married, native-country =  United-States, relationship =  Own-child, sex =  Male\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m7.32%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m8.26%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m27.27%\u001b[39m and counterfactual cost = 11.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m47.11%\u001b[39m and counterfactual cost = 11.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m63.64%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m75.21%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m8.99%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m4.21%\u001b[39m and counterfactual cost = 11.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m14.25%\u001b[39m and counterfactual cost = 11.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m28.00%\u001b[39m and counterfactual cost = 11.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m43.87%\u001b[39m and counterfactual cost = 11.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m49.44%\u001b[39m and counterfactual cost = 11.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m97.40%\u001b[39m and counterfactual cost = 11.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 12.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.71.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 26928 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, capital-loss = 0, marital-status =  Never-married\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m44.46%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m3.27%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m14.01%\u001b[39m and counterfactual cost = 1.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 4386\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m19.59%\u001b[39m and counterfactual cost = 1.04.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m24.22%\u001b[39m and counterfactual cost = 1.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m40.54%\u001b[39m and counterfactual cost = 1.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m43.54%\u001b[39m and counterfactual cost = 1.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m94.15%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m94.15%\u001b[39m and counterfactual cost = 1.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m94.15%\u001b[39m and counterfactual cost = 1.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m94.15%\u001b[39m and counterfactual cost = 1.45.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m37.12%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m3.15%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m12.79%\u001b[39m and counterfactual cost = 1.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 4386\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m17.83%\u001b[39m and counterfactual cost = 1.04.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m22.09%\u001b[39m and counterfactual cost = 1.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m33.97%\u001b[39m and counterfactual cost = 1.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m36.01%\u001b[39m and counterfactual cost = 1.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m83.37%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m83.37%\u001b[39m and counterfactual cost = 1.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m83.37%\u001b[39m and counterfactual cost = 1.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m83.37%\u001b[39m and counterfactual cost = 1.45.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.71.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 27956 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, capital-gain = 0, capital-loss = 0, marital-status =  Never-married\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m36.12%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m2.51%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m37.19%\u001b[39m and counterfactual cost = 1.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m40.03%\u001b[39m and counterfactual cost = 1.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m93.97%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m93.97%\u001b[39m and counterfactual cost = 1.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m93.97%\u001b[39m and counterfactual cost = 1.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m93.97%\u001b[39m and counterfactual cost = 1.45.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m93.97%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m93.97%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m93.97%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m93.97%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m93.97%\u001b[39m and counterfactual cost = 2.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m31.19%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m2.21%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m30.39%\u001b[39m and counterfactual cost = 1.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m32.43%\u001b[39m and counterfactual cost = 1.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m82.07%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1887\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m82.07%\u001b[39m and counterfactual cost = 1.43.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1902\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m82.07%\u001b[39m and counterfactual cost = 1.44.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-loss = 1977\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m82.07%\u001b[39m and counterfactual cost = 1.45.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m82.07%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m82.07%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m82.07%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m82.07%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m82.07%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.7.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25616 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, native-country =  United-States, occupation =  Other-service\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m14.28%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Transport-moving\u001b[39m\u001b[0m with effectiveness \u001b[32m0.85%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m1.69%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m2.12%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m3.39%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Protective-serv\u001b[39m\u001b[0m with effectiveness \u001b[32m4.66%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m7.20%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m7.63%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m9.32%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m38.14%\u001b[39m and counterfactual cost = 1.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m89.83%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m91.53%\u001b[39m and counterfactual cost = 1.15.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m10.81%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Transport-moving\u001b[39m\u001b[0m with effectiveness \u001b[32m1.13%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m1.44%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m1.75%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m2.47%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Protective-serv\u001b[39m\u001b[0m with effectiveness \u001b[32m2.89%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m3.30%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m3.40%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m5.77%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m25.88%\u001b[39m and counterfactual cost = 1.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m70.72%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m75.05%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.69.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25704 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
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     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mcapital-gain = 0, marital-status =  Never-married\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m45.80%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m4.23%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m15.32%\u001b[39m and counterfactual cost = 1.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 4386\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m20.87%\u001b[39m and counterfactual cost = 1.04.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m25.36%\u001b[39m and counterfactual cost = 1.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m42.01%\u001b[39m and counterfactual cost = 1.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m44.91%\u001b[39m and counterfactual cost = 1.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m94.19%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m38.34%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m3.81%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 3103\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m13.92%\u001b[39m and counterfactual cost = 1.03.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 4386\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m19.06%\u001b[39m and counterfactual cost = 1.04.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 5178\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m23.45%\u001b[39m and counterfactual cost = 1.05.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m35.18%\u001b[39m and counterfactual cost = 1.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m37.19%\u001b[39m and counterfactual cost = 1.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m83.76%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 99999\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.66.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 27128 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, capital-gain = 0, marital-status =  Never-married\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m37.14%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m3.26%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m38.60%\u001b[39m and counterfactual cost = 1.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m41.37%\u001b[39m and counterfactual cost = 1.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m93.97%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m93.97%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m93.97%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m93.97%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m93.97%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m93.97%\u001b[39m and counterfactual cost = 2.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m32.20%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m2.91%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m31.58%\u001b[39m and counterfactual cost = 1.07.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 7688\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m33.59%\u001b[39m and counterfactual cost = 1.08.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m82.46%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m82.46%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m82.46%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m82.46%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m82.46%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m82.46%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.65.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 24704 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mage = (16.999, 26.0], capital-gain = 0, marital-status =  Never-married\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m20.69%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m1.17%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m3.22%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m58.48%\u001b[39m and counterfactual cost = 2.07.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m100.00%\u001b[39m and counterfactual cost = 2.15.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m21.87%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (26.0, 34.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m0.51%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m2.39%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mcapital-gain = 7298\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m43.35%\u001b[39m and counterfactual cost = 2.07.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m\u001b[0m with effectiveness \u001b[32m96.13%\u001b[39m and counterfactual cost = 2.15.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.64.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 25004 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
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     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, capital-gain = 0, occupation =  Other-service\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m15.31%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Transport-moving\u001b[39m\u001b[0m with effectiveness \u001b[32m0.79%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m2.37%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m3.16%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m4.74%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m9.09%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m9.09%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m9.49%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m90.91%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m90.91%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m90.91%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m90.91%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m90.91%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31moccupation =  Protective-serv\u001b[39m\u001b[0m with effectiveness \u001b[32m90.91%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m90.91%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m90.91%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m90.91%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m90.91%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m90.91%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m90.91%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m90.91%\u001b[39m and counterfactual cost = 2.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m10.21%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Transport-moving\u001b[39m\u001b[0m with effectiveness \u001b[32m0.87%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m1.20%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m1.20%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m1.74%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m2.29%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m2.29%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m4.58%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m72.63%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m72.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m72.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m72.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m72.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31moccupation =  Protective-serv\u001b[39m\u001b[0m with effectiveness \u001b[32m72.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m72.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m72.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m72.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m72.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m72.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m72.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m72.63%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.63.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 24328 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, capital-gain = 0, capital-loss = 0, occupation =  Other-service\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m15.00%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m2.02%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m2.82%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m4.44%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m8.87%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m8.87%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m9.27%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m90.73%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m90.73%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m90.73%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m90.73%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31moccupation =  Protective-serv\u001b[39m\u001b[0m with effectiveness \u001b[32m90.73%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m90.73%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m90.73%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m90.73%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m90.73%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m90.73%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m90.73%\u001b[39m and counterfactual cost = 2.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m9.96%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Craft-repair\u001b[39m\u001b[0m with effectiveness \u001b[32m0.78%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m0.78%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m1.34%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m1.90%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Tech-support\u001b[39m\u001b[0m with effectiveness \u001b[32m1.90%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m4.03%\u001b[39m and counterfactual cost = 1.0.\n",
      "\t\tMake \u001b[1m\u001b[31mcapital-gain = 15024\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m72.26%\u001b[39m and counterfactual cost = 1.15.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m72.26%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-not-inc\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m72.26%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  State-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m72.26%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31moccupation =  Protective-serv\u001b[39m\u001b[0m with effectiveness \u001b[32m72.26%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m72.26%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Sales\u001b[39m\u001b[0m with effectiveness \u001b[32m72.26%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31moccupation =  Adm-clerical\u001b[39m\u001b[0m with effectiveness \u001b[32m72.26%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Local-gov\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m72.26%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Self-emp-inc\u001b[39m, \u001b[31moccupation =  Exec-managerial\u001b[39m\u001b[0m with effectiveness \u001b[32m72.26%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\tMake \u001b[1m\u001b[31mWorkclass =  Federal-gov\u001b[39m, \u001b[31moccupation =  Prof-specialty\u001b[39m\u001b[0m with effectiveness \u001b[32m72.26%\u001b[39m and counterfactual cost = 2.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.63.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 24200 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If \u001b[1mWorkclass =  Private, age = (16.999, 26.0], education-num = 9, hours-per-week = FullTime, marital-status =  Never-married, relationship =  Own-child\u001b[0m:\n",
      "\tProtected Subgroup '\u001b[1m Non-White\u001b[0m', \u001b[34m2.24%\u001b[39m covered out of 1748\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m37.84%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 10\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m37.84%\u001b[39m and counterfactual cost = 32.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m62.16%\u001b[39m and counterfactual cost = 33.0.\n",
      "\tProtected Subgroup '\u001b[1m White\u001b[0m', \u001b[34m1.58%\u001b[39m covered out of 8977\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m5.63%\u001b[39m and counterfactual cost = 13.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 10\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m5.63%\u001b[39m and counterfactual cost = 32.0.\n",
      "\t\tMake \u001b[1m\u001b[31mage = (34.0, 41.0]\u001b[39m, \u001b[31meducation-num = 10\u001b[39m, \u001b[31mhours-per-week = OverTime\u001b[39m, \u001b[31mmarital-status =  Married-civ-spouse\u001b[39m, \u001b[31mrelationship =  Married\u001b[39m\u001b[0m with effectiveness \u001b[32m14.79%\u001b[39m and counterfactual cost = 33.0.\n",
      "\t\u001b[35m Unfairness based on the Kolmogorov-Smirnov test = 2.62.\u001b[39m\n",
      "\t\u001b[36mCumulative effectiveness plot for the above recourses:\u001b[39m\n"
     ]
    },
    {
     "data": {
      "image/png": "[encoded data, 24236 characters]",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "affected_pop_sizes = {sg: ((X_test[\"race\"] == sg) & (preds_Xtest == 0)).sum() for sg in X_test[\"race\"].unique()}\n",
    "\n",
    "top_rules,unfairness = facts.select_rules_subset_KStest(\n",
    "    rules_with_cumulative,\n",
    "    affected_pop_sizes,\n",
    "    top_count=50\n",
    ")\n",
    "\n",
    "print_recourse_report_KStest_cumulative(\n",
    "    top_rules,\n",
    "    population_sizes=pop_sizes,\n",
    "    unfairness = unfairness,\n",
    "    show_then_costs=True,\n",
    "    show_cumulative_plots=True\n",
    ")"
   ]
  }
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