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unique_labels — scikit-learn 1.7.1 documentation
unique_labels ([ 1 , 2 , 3 , 4 ], [ 2 , 2 , 3 , 4 ]) array([1, 2, 3, 4])...unique_labels ([ 1 , 2 , 10 ], [ 5 , 11 ]) array([ 1, 2, 5, 10, 11])...scikit-learn.org/stable/modules/generated/sklearn.utils.multiclass.unique_labels.html -
Multiclass Receiver Operating Characteristic (R...
1 ], [ 0 , 1 ], "k--" , label = "Chance...xlim = ( - 0.01 , 1.01 ), ylim = ( - 0.01 , 1.01 ), ) We confirm...scikit-learn.org/stable/auto_examples/model_selection/plot_roc.html -
manhattan_distances — scikit-learn 1.7.1 docume...
]]) array([[1.]]) >>> manhattan_distances ([[ 1 , 2 ], [ 3 ,...manhattan_distances ([[ 3 ]], [[ 2 ]]) array([[1.]]) >>> manhattan_distances ([[...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.manhattan_distances.html -
Pipeline ANOVA SVM — scikit-learn 1.7.1 documen...
anova_svm [: - 1 ] . inverse_transform ( anova_svm [ - 1 ] . coef_...'squared_hinge' dual 'auto' tol 0.0001 C 1.0 multi_class 'ovr' fit_intercept...scikit-learn.org/stable/auto_examples/feature_selection/plot_feature_selection_pipeline.html -
Release Highlights for scikit-learn 0.22 — scik...
pclass embarked 0 1 S 1 1 S 2 1 S 3 1 S 4 1 S Checking scikit-learn...array ([ 0 , 1 , 2 , np . nan ]) . reshape ( - 1 , 1 ) y = [ 0 ,...scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_0_22_0.html -
Gradient Boosting Out-of-Bag estimates — scikit...
subsample < 1.0 ), the estimates are derived...y = random_state . binomial ( 1 , p , size = n_samples ) X = np...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_oob.html -
Version 0.21 — scikit-learn 1.7.1 documentation
threaded for n_jobs > 1 or n_jobs = -1 . #12955 by Prabakaran...linear_model.ARDRegression and Scipy>=1.3.0. Adapts to upstream changes...scikit-learn.org/stable/whats_new/v0.21.html -
Displaying estimators and complex pipelines — s...
0001 C 1.0 fit_intercept True intercept_scaling 1 class_weight...ColumnTransformer(transformers=[('pipeline-1', Pipeline(steps=[('simpleimputer',...scikit-learn.org/stable/auto_examples/miscellaneous/plot_estimator_representation.html -
parametrize_with_checks — scikit-learn 1.7.1 do...
scikit-learn 1.6 Release Highlights for scikit-learn 1.6 On this...specific category. Added in version 1.6. expected_failed_checks callable,...scikit-learn.org/stable/modules/generated/sklearn.utils.estimator_checks.parametrize_with_checks.... -
Version 0.20 — scikit-learn 1.7.1 documentation
1} or {-1, 1} through pos_label parameter....PyPy3-v5.10+, Numpy 1.14.0+, and scipy 1.1.0+ are required. #11010...scikit-learn.org/stable/whats_new/v0.20.html