# SHAP

> Game theoretic approach to explain ML model outputs

- Category: [Observability & Evals](https://ailandscape.org/category/observability-evals) › Explainability & Alignment
- Homepage: https://shap.readthedocs.io
- Repository: https://github.com/shap/shap
- Tags: explainability, xai
- Added to the landscape: 2026-03-18

## Similar tools in Explainability & Alignment

- [Captum](https://ailandscape.org/tool/captum): Model interpretability library for PyTorch
- [ELI5](https://ailandscape.org/tool/eli5): Debug and explain ML classifiers and regressors
- [InterpretML](https://ailandscape.org/tool/interpretml): Microsoft's toolkit for model interpretability
- [LIME](https://ailandscape.org/tool/lime): Local interpretable model-agnostic explanations

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Part of [AI Landscape](https://ailandscape.org), an open map of the AI ecosystem. Web page: https://ailandscape.org/tool/shap · Index for AI assistants: https://ailandscape.org/llms.txt