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Model Selection#

Examples related to the sklearn.model_selection module.

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Balance model complexity and cross-validated score

Balance model complexity and cross-validated score
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Class Likelihood Ratios to measure classification performance

Class Likelihood Ratios to measure classification performance
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Comparing randomized search and grid search for hyperparameter estimation

Comparing randomized search and grid search for hyperparameter estimation
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Comparison between grid search and successive halving

Comparison between grid search and successive halving
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Custom refit strategy of a grid search with cross-validation

Custom refit strategy of a grid search with cross-validation
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Demonstration of multi-metric evaluation on cross_val_score and GridSearchCV

Demonstration of multi-metric evaluation on cross_val_score and GridSearchCV
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Detection error tradeoff (DET) curve

Detection error tradeoff (DET) curve
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Effect of model regularization on training and test error

Effect of model regularization on training and test error
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Evaluate the performance of a classifier with Confusion Matrix

Evaluate the performance of a classifier with Confusion Matrix
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Multiclass Receiver Operating Characteristic (ROC)

Multiclass Receiver Operating Characteristic (ROC)
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Nested versus non-nested cross-validation

Nested versus non-nested cross-validation
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Plotting Cross-Validated Predictions

Plotting Cross-Validated Predictions
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Plotting Learning Curves and Checking Models Scalability

Plotting Learning Curves and Checking Models' Scalability
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Post-hoc tuning the cut-off point of decision function

Post-hoc tuning the cut-off point of decision function
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Post-tuning the decision threshold for cost-sensitive learning

Post-tuning the decision threshold for cost-sensitive learning
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Precision-Recall

Precision-Recall
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Receiver Operating Characteristic (ROC) with cross validation

Receiver Operating Characteristic (ROC) with cross validation
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Sample pipeline for text feature extraction and evaluation

Sample pipeline for text feature extraction and evaluation
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Statistical comparison of models using grid search

Statistical comparison of models using grid search
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Successive Halving Iterations

Successive Halving Iterations
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Test with permutations the significance of a classification score

Test with permutations the significance of a classification score
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Underfitting vs. Overfitting

Underfitting vs. Overfitting
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Visualizing cross-validation behavior in scikit-learn

Visualizing cross-validation behavior in scikit-learn

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Imputing missing values with variants of IterativeImputer

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Balance model complexity and cross-validated score

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