This is documentation for an old release of Scikit-learn (version 1.3). Try the latest stable release (version 1.6) or development (unstable) versions.

Model Selection

Examples related to the sklearn.model_selection module.

Balance model complexity and cross-validated score

Balance model complexity and cross-validated score

Class Likelihood Ratios to measure classification performance

Class Likelihood Ratios to measure classification performance

Comparing randomized search and grid search for hyperparameter estimation

Comparing randomized search and grid search for hyperparameter estimation

Comparison between grid search and successive halving

Comparison between grid search and successive halving

Confusion matrix

Confusion matrix

Custom refit strategy of a grid search with cross-validation

Custom refit strategy of a grid search with cross-validation

Demonstration of multi-metric evaluation on cross_val_score and GridSearchCV

Demonstration of multi-metric evaluation on cross_val_score and GridSearchCV

Detection error tradeoff (DET) curve

Detection error tradeoff (DET) curve

Multiclass Receiver Operating Characteristic (ROC)

Multiclass Receiver Operating Characteristic (ROC)

Nested versus non-nested cross-validation

Nested versus non-nested cross-validation

Plotting Cross-Validated Predictions

Plotting Cross-Validated Predictions

Plotting Learning Curves and Checking Models’ Scalability

Plotting Learning Curves and Checking Models' Scalability

Plotting Validation Curves

Plotting Validation Curves

Precision-Recall

Precision-Recall

Receiver Operating Characteristic (ROC) with cross validation

Receiver Operating Characteristic (ROC) with cross validation

Sample pipeline for text feature extraction and evaluation

Sample pipeline for text feature extraction and evaluation

Statistical comparison of models using grid search

Statistical comparison of models using grid search

Successive Halving Iterations

Successive Halving Iterations

Test with permutations the significance of a classification score

Test with permutations the significance of a classification score

Train error vs Test error

Train error vs Test error

Underfitting vs. Overfitting

Underfitting vs. Overfitting

Visualizing cross-validation behavior in scikit-learn

Visualizing cross-validation behavior in scikit-learn