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Shapash is a Python library dedicated to the interpretability of Data Science models. It provides several types of visualization that display explicit labels that everyone can understand. Data Scientists can more easily understand their models, share their results and easily document their projects in an HTML report. End users can understand the suggestion proposed by a model using a summary of the most influential criteria.
Features
- Compatible with Shap and Lime
- Uses shap backend to display results in a few lines of code
- Encoders objects and features dictionaries used for clear results
- Compatible with category_encoders & Sklearn ColumnTransformer
- Visualizations of global and local explainability
- Webapp to easily navigate from global to local
- Summarizes local explanation
- Offers several parameters in order to summarize in the most suitable way for your use case
Project Samples
Categories
Machine LearningLicense
Apache License V2.0Follow Shapash
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