Author: Frank van Mourik, University of Twente
Install via pip using: pip install itershap (requires Python version >=3.10,<3.11).
from itershap import IterSHAP
X, y = get_data() # Replace with data location
fs = IterSHAP() # Create a IterSHAP feature selection object
fs.fit(X, y) # Execute IterSHAP on input data
X_transformed = fs.transform(X) # Only keep the via IterSHAP selected features- Performs well on small high-dimensional datasets
- Guarantees to return a feature subset
- Model-agnostic (limited by shap supported models)
- Validated on synthesised data
- Benchmarked on DEAP dataset
Available under the MIT license, which can be found here