Individual skill
matlab-interpret-machine-learning-model
Interpret and explain a trained tabular machine-learning model (classification or regression) in MATLAB. Find which predictors, features, or columns matter most; explain why the model made a specific prediction, including diagnosing predictions it got wrong; show how a predictor affects the output; and compare how the model behaves across cohorts or subgroups. Uses model-agnostic techniques and model-native measures, and works on custom models (such as a dlnetwork) through a prediction function handle. Use for model interpretability, explainability, and feature-importance questions on tabular data, not for training, tuning, feature selection, deploying models, or models trained on image, text, signal, or other non-tabular data.
skills-catalog/ai-and-statistics/matlab-interpret-machine-learning-model/SKILL.md
Source commit 032b4b605999b1f4adecaac1efa1c9faad41adf6
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- Observed behavior
- Instructions only
- Last checked
- Nov 3, 2026
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- 1,275
- Repository last updated
- Nov 5, 2026
- License
- NOASSERTION
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- agent-skills Repository topic
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- codex-plugin Repository topic
- github-copilot Repository topic
- matlab Repository topic
- matlab-mcp-server Repository topic
- engineering-agents Repository topic
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SKILL.mdcore · 32,539 bytesmanifest.yamlasset · 556 bytesreferences/agnostic-effect-shape.mddoc · 6,958 bytesreferences/agnostic-global-importance.mddoc · 9,809 bytesreferences/agnostic-local-explanation.mddoc · 6,795 bytesreferences/cohort-analysis.mddoc · 4,633 bytesreferences/custom-model-wrapper.mddoc · 9,588 bytesreferences/native-importance-measures.mddoc · 10,166 bytesscripts/functionHandleMap.masset · 4,003 bytes
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