data-science-model-evaluation
Model Evaluation
Use this skill for rigorously assessing model performance, comparing alternatives, and diagnosing issues.
When to use this skill
- Model training complete — need performance assessment
- Comparing multiple models/algorithms
- Diagnosing overfitting/underfitting
- Hyperparameter tuning
- Production readiness check
Evaluation workflow
- Cross-validation strategy
- K-fold (default for most cases)
- Stratified K-fold (classification with imbalance)
- TimeSeriesSplit (temporal data)
- GroupKFold (grouped/clustered data)
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