shap
Description
Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or
How to Use
- Visit the GitHub repository to get the SKILL.md file
- Copy the file to your project root or .cursor/rules directory
- Restart your AI assistant or editor to apply the new skill
Tags
About shap
shap is an AI skill in the ml-data category, designed to help developers and users work more effectively with AI tools. Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or
This skill has earned 2,800 stars on GitHub, reflecting strong community adoption and trust. It is compatible with claude.
Key Capabilities
Why Use shap
Adding shap to your AI workflow can significantly enhance your productivity in ml-data tasks. With pre-defined prompt templates and best practices, this skill helps AI assistants better understand your requirements and deliver more accurate responses.
Whether you use claude, you can easily integrate this skill into your existing development environment.
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