shap and FastTreeSHAP
FastTreeSHAP is a specialized accelerator for the general-purpose SHAP library, optimizing Shapley value computation specifically for tree-based models that SHAP already supports.
About shap
shap/shap
A game theoretic approach to explain the output of any machine learning model.
Based on the README, here's a technical summary: Implements fast exact algorithms for tree ensemble models (XGBoost, LightGBM, CatBoost, scikit-learn, PySpark) via optimized C++ backends, alongside approximation methods for deep learning (DeepExplainer leveraging DeepLIFT) and NLP transformers using coalitional game rules. Provides multiple visualization outputs—waterfall plots, force plots, dependence scatter plots, and beeswarm distributions—to show feature contributions at instance and global levels. Integrates directly with popular ML frameworks and Hugging Face transformers, supporting both tabular and text-based model explanations.
About FastTreeSHAP
linkedin/FastTreeSHAP
Fast SHAP value computation for interpreting tree-based models
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