Metadata-Version: 2.1
Name: ml-feature-toolkit
Version: 0.0.1
Summary: A package for analyzing feature interactions in machine learning models
Home-page: https://github.com/HishamSalem/pymltools
Author: Hisham Salem
Author-email: hisham.salem@mail.mcgill.ca
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: scikit-learn
Requires-Dist: xgboost
Requires-Dist: shap
Requires-Dist: optbinning
Requires-Dist: SALib
Requires-Dist: scipy
Requires-Dist: statsmodels
Requires-Dist: tqdm
Requires-Dist: matplotlib
Requires-Dist: seaborn
Requires-Dist: joblib

# pymltools

A comprehensive Python toolkit for analyzing feature interactions in machine learning models, combining multiple methodologies to provide deep insights into feature relationships and their impact on model behavior.

## Features

### Interaction Analysis Methods
- **SHAP Interaction Analysis**: Leverages SHAP values to detect and quantify feature interactions
- **Feature Binning Analysis**: Uses optimal binning techniques to identify non-linear relationships
- **Sensitivity Analysis**: Implements Sobol indices to measure feature interaction effects

### Key Capabilities
- Statistical significance testing for interactions
- Visualization of interaction effects
- Multiple testing correction

## Installation

```bash
pip install ml-feature-toolkit

