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conda-forge.org : shap
SHAP (SHapley Additive exPlanations) is a unified approach to explain the output of any machine learning model. SHAP connects game theory with local explanations, uniting several previous methods and representing the only possible consistent and locally accurate additive feature attribution method based on expectations.
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Source
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purl: pkg:conda/shap
Keywords: deep-learning, explainability, gradient-boosting, interpretability, machine-learning, shap, shapley
License: MIT
Latest release: almost 2 years ago
First release: over 5 years ago
Dependent packages: 16
Dependent repositories: 51
Stars: 18,811 on GitHub
Forks: 2,835 on GitHub
See more repository details: repos.ecosyste.ms
Last synced: 11 days ago