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Awesome GitHub RepositoriesExplainable AI Toolkits
Collections of methods and algorithms designed to interpret and visualize the decision-making processes of machine learning models.
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Awesome Explainable AI Toolkits GitHub Repositories
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- shap/shap
shap/shap
25,049View on GitHubSHAP is an explainable AI toolkit that provides a game theoretic framework for interpreting machine learning model predictions. It functions as a feature attribution engine, decomposing model outputs into the sum of individual feature effects to clarify how specific input variables influence a final decision. By assigning importance values to these inputs, the library enables users to understand the logic behind complex predictive models. The project distinguishes itself through its versatility and specialized calculation methods. It operates as a model-agnostic diagnostic library, capable of
Provides mathematical methods to assign importance values to input features for interpreting machine learning model predictions.
Jupyter Notebookdeep-learningexplainabilitygradient-boosting
