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shap / shap

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

Repository stars
25,850All-time #1,567
Fork
3,790
Last push
updated 2 days ago
Repository created
since 2016
Apps & systemsGames & interactive experiencesJupyter NotebookMIT · Permissive
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About

Summarised by AI from the README; the original prevails

Author description: A game theoretic approach to explain the output of any machine learning model.

Basic listing based on official public information; functionality has not been independently evaluated.

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Star trend

Includes values estimated from GitHub history
25,78325,81425,84510-0710-1210-1710-2210-2711-0111-05
Raw observations · 2
Historical observations
Measured atRepository starsSource
2026-11-06 08:41 UTC25,850Source
2026-11-02 19:02 UTC25,845Source

First collected 2026-11-03Measured at 2026-11-06 08:41 UTCSourceLicense source

Compiled from public project information; not independently tested. · Repository stars, not unique users or individual-skill installs · License tiers are derived from metadata. Check obligations for your use; unknown does not mean prohibited.