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A unified approach to explain the output of any machine learning model.

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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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Files for shap, version 0.29.3
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Filename, size shap-0.29.3-cp35-cp35m-win_amd64.whl (260.1 kB) File type Wheel Python version 3.5 Upload date Hashes View hashes
Filename, size shap-0.29.3-cp36-cp36m-win_amd64.whl (260.2 kB) File type Wheel Python version 3.6 Upload date Hashes View hashes
Filename, size shap-0.29.3-cp37-cp37m-macosx_10_7_x86_64.whl (262.4 kB) File type Wheel Python version 3.7 Upload date Hashes View hashes
Filename, size shap-0.29.3-cp37-cp37m-win_amd64.whl (260.2 kB) File type Wheel Python version 3.7 Upload date Hashes View hashes
Filename, size shap-0.29.3.tar.gz (230.4 kB) File type Source Python version None Upload date Hashes View hashes

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