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Multiclass Receiver Operating Characteristic (R...
This example describes the use of the Receiver Operating Characteristic (ROC) metric to evaluate the quality of multiclass classifiers. ROC curves typically feature true positive rate (TPR) on the ...scikit-learn.org/stable/auto_examples/model_selection/plot_roc.html -
Balance model complexity and cross-validated sc...
This example balances model complexity and cross-validated score by finding a decent accuracy within 1 standard deviation of the best accuracy score while minimising the number of PCA components [1...scikit-learn.org/stable/auto_examples/model_selection/plot_grid_search_refit_callable.html -
Target Encoder’s Internal Cross fitting — sciki...
The TargetEncoder replaces each category of a categorical feature with the shrunk mean of the target variable for that category. This method is useful in cases where there is a strong relationship ...scikit-learn.org/stable/auto_examples/preprocessing/plot_target_encoder_cross_val.html -
mean_absolute_percentage_error — scikit-learn 1...
Gallery examples: Lagged features for time series forecastingscikit-learn.org/stable/modules/generated/sklearn.metrics.mean_absolute_percentage_error.html -
d2_log_loss_score — scikit-learn 1.5.2 document...
Skip to main content Back to top Ctrl + K GitHub d2_log_loss_score # sklearn.metrics. d2_log_loss_score ( y_true , y_...scikit-learn.org/stable/modules/generated/sklearn.metrics.d2_log_loss_score.html -
2.7. Novelty and Outlier Detection — scikit-lea...
Many applications require being able to decide whether a new observation belongs to the same distribution as existing observations (it is an inlier), or should be considered as different (it is an ...scikit-learn.org/stable/modules/outlier_detection.html -
Hashing feature transformation using Totally Ra...
RandomTreesEmbedding provides a way to map data to a very high-dimensional, sparse representation, which might be beneficial for classification. The mapping is completely unsupervised and very effi...scikit-learn.org/stable/auto_examples/ensemble/plot_random_forest_embedding.html -
A demo of structured Ward hierarchical clusteri...
Compute the segmentation of a 2D image with Ward hierarchical clustering. The clustering is spatially constrained in order for each segmented region to be in one piece. Generate data: Resize it to ...scikit-learn.org/stable/auto_examples/cluster/plot_coin_ward_segmentation.html -
Plot multi-class SGD on the iris dataset — scik...
Plot decision surface of multi-class SGD on iris dataset. The hyperplanes corresponding to the three one-versus-all (OVA) classifiers are represented by the dashed lines. Total running time of the ...scikit-learn.org/stable/auto_examples/linear_model/plot_sgd_iris.html -
Comparing randomized search and grid search for...
Compare randomized search and grid search for optimizing hyperparameters of a linear SVM with SGD training. All parameters that influence the learning are searched simultaneously (except for the nu...scikit-learn.org/stable/auto_examples/model_selection/plot_randomized_search.html