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shap · PyPI An implementation of Deep SHAP, a faster (but only approximate) algorithm to compute SHAP values for deep learning models that is based on connections between SHAP and the DeepLIFT algorithm
SHAP : A Comprehensive Guide to SHapley Additive exPlanations SHAP (SHapley Additive exPlanations) has a variety of visualization tools that help interpret machine learning model predictions These plots highlight which features are important and also explain how they influence individual or overall model outputs
全流程：机器学习之可解释性分析-SHAP值，彻底了解每个图的含义 特征重要性-特征交互_哔哩哔哩_bilibili 全流程：机器学习之 可解释性分析-SHAP 值，彻底了解每个图的含义 特征重要性-特征交互 用起来不再迷茫 https: shap readthedocs io en latest example_notebooks tabular_examples tree_based_models Census%20income%20classification%20with%20XGBoost html
Shapley Additive Explanation - an overview - ScienceDirect Shapley additive explantaion (SHAP) The SHapley Additive exPlanations (SHAP) framework provides a universal approach for interpreting the results of machine learning models, even those considered opaque or ”black box” models such as neural networks