# Run IDS for Apdative Sampling for Discovery

## Code Organizations
Use `Experiments/expt_*.py` to run IDS under different models. We implemented 
- `expt_graph.py` for graph models
- `expt_linear.py` for linear models
- `expt_logistic.py` for logistic regressin models
- `expt_matrix.py` for low-rank matrix models
- `expt_real_data_CNCCI.py` for CNCCI dataset as a linear regression model
- `expt_real_data_PNDC.py` for PNDC dataset as a linear regression model

Hyperparameters are setup in `expt_*.py` for each algorithm. Run `python Experiments/expt_*.py` to generate results.

## Datasets

The two datasets are included in **PNDC.xlsx** and **CNCCI.xlsx** under data folder in the  code. Each file has two sheets for yield and descriptors respectively.
