Shypd.aiThe largest open index of AI toolsShapash is a Python library that provides user-friendly explainability and interpretability for machine learning models. It generates a web application for seamless navigation between local and global explainability, making models comprehensible for both data scientists and non-experts.
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Shapash is a Python library designed to make machine learning models interpretable and comprehensible for everyone. It offers various visualizations with clear and explicit labels, simplifying the understanding of interactions between a model's features. A key feature is its ability to generate a Webapp, allowing users to easily navigate between local and global explainability. This Webapp helps Data Scientists understand their models and share results with non-data experts. Shapash also contributes to data science auditing by providing comprehensive reports about models and data. It supports Regression, Binary Classification, and Multiclass problems and is compatible with numerous models like Catboost, Xgboost, LightGBM, Sklearn Ensemble, Linear models, and SVM, with options to integrate other models.
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