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AI & Machine Learning
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shap

Model interpretability and explainability using SHAP

Category

AI & Machine Learning

Author

davila7

Updated

Jan 2026

Tags

4

Install Command

claude skill add davila7/claude-code-templates

Description

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.

Tags

model interpretabilityexplainable AIfeature importanceSHAP plots

Information

Developerdavila7
CategoryAI & Machine Learning
CreatedJan 15, 2026
UpdatedJan 15, 2026

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