evaluate_model
Assess a trained model's accuracy and reliability using cross-validation, detailed metrics, and statistical significance tests.
Instructions
Evaluate a single trained model with comprehensive metrics and cross-validation
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| model_path | Yes | Path to the trained model file (.pkl) | |
| dataset_name | No | Name of the loaded dataset for evaluation | |
| dataset_path | No | Path to the evaluation dataset file - alternative to dataset_name | |
| target_column | Yes | Name of the target/label column | |
| cv_folds | No | Number of cross-validation folds | |
| enable_statistical_tests | No | Perform statistical significance tests | |
| significance_level | No | Significance level for statistical tests | |
| generate_learning_curves | No | Generate learning curves | |
| detailed_metrics | No | Calculate detailed metrics and reports | |
| scoring_metrics | No | List of scoring metrics for evaluation | |
| learning_curve_train_sizes | No | Training sizes for learning curves | |
| save_results | No | Save evaluation results |