Computation timesΒΆ
02:40.755 total execution time for auto_examples_model_selection files:
00:35.637: Demonstration of multi-metric evaluation on cross_val_score and GridSearchCV (
plot_multi_metric_evaluation.py
)00:35.419: Comparing randomized search and grid search for hyperparameter estimation (
plot_randomized_search.py
)00:29.920: Balance model complexity and cross-validated score (
plot_grid_search_refit_callable.py
)00:20.503: Plotting Validation Curves (
plot_validation_curve.py
)00:10.573: Plotting Learning Curves (
plot_learning_curve.py
)00:08.220: Train error vs Test error (
plot_train_error_vs_test_error.py
)00:07.850: Nested versus non-nested cross-validation (
plot_nested_cross_validation_iris.py
)00:06.705: Parameter estimation using grid search with cross-validation (
plot_grid_search_digits.py
)00:02.058: Visualizing cross-validation behavior in scikit-learn (
plot_cv_indices.py
)00:00.955: Precision-Recall (
plot_precision_recall.py
)00:00.790: Underfitting vs. Overfitting (
plot_underfitting_overfitting.py
)00:00.620: Receiver Operating Characteristic (ROC) (
plot_roc.py
)00:00.617: Receiver Operating Characteristic (ROC) with cross validation (
plot_roc_crossval.py
)00:00.604: Confusion matrix (
plot_confusion_matrix.py
)00:00.283: Plotting Cross-Validated Predictions (
plot_cv_predict.py
)00:00.000: Sample pipeline for text feature extraction and evaluation (
grid_search_text_feature_extraction.py
)