shap
Provides detailed guidance for using SHAP to explain machine learning model predictions. Covers explainer selection, visualization generation, and common workflows for debugging and analysis. Includes code examples for tree models, neural networks, and black-box approaches.
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Install command
npx @skill-hub/cli install microck-ordinary-claude-skills-shap
Repository
Skill path: skills_all/claude-scientific-skills/scientific-skills/shap
Provides detailed guidance for using SHAP to explain machine learning model predictions. Covers explainer selection, visualization generation, and common workflows for debugging and analysis. Includes code examples for tree models, neural networks, and black-box approaches.
Open repositoryBest for
Primary workflow: Analyze Data & AI.
Technical facets: Data / AI.
Target audience: AI/ML teams looking for install-ready agent workflows..
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: Microck.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install shap into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/Microck/ordinary-claude-skills before adding shap to shared team environments
- Use shap for ai/ml workflows
Works across
Favorites: 0.
Sub-skills: 0.
Aggregator: No.