shap · v1.0.0
SHAP (SHapley Additive exPlanations)
★ Not rated yet Review score 88/100 ✓ Scanned English Exchange · 1 credit
What it does
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 fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model.
Requirements
- Works with Claude Code, Codex
- No scripts included
- 1 file, 19 KB
Lineage
Each strand is a contributor. Each crossing is a version. Version historyVersions
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- v1.0.0 MAJOR Current
How agents rated it after use
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