model-evaluator
Model Evaluator
Overview
Provides comprehensive, unbiased model evaluation following ML best practices. Goes beyond simple accuracy to evaluate models across multiple dimensions, ensuring confident deployment decisions.
Core Evaluation Framework
1. Classification Metrics
- Accuracy, Precision, Recall, F1-score
- ROC AUC, PR AUC
- Confusion matrix
- Per-class metrics (for multi-class)
- Class imbalance handling
2. Regression Metrics
- RMSE, MAE, MAPE
- R² score, Adjusted R²
- Residual analysis
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