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config_context — scikit-learn 1.7.0 documentation
Added in version 1.1. enable_cython_pairwise_dist...configuration setting. Added in version 1.1. array_api_dispatch bool, default=None...scikit-learn.org/stable/modules/generated/sklearn.config_context.html -
label_ranking_average_precision_score — scikit-...
1 ], [ 1 , 0.2 , 0.1 ]]) >>> label_ranki...y_true = np . array ([[ 1 , 0 , 0 ], [ 0 , 0 , 1 ]]) >>> y_score =...scikit-learn.org/stable/modules/generated/sklearn.metrics.label_ranking_average_precision_score.html -
cosine_similarity — scikit-learn 1.7.0 document...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.cosine_similarity.html -
make_regression — scikit-learn 1.7.0 documentation
1.523], [-0.2341, -0.2341], [-0.4694, 0.5425], [ 1.579,...scikit-learn 1.4 Release Highlights for scikit-learn 1.4 On this...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_regression.html -
Iso-probability lines for Gaussian Processes cl...
1 , ( 1e-5 , np . inf )) * DotProduct ( sigma_0 = 0.1 ) **...( 0 , 1 ) plt . plot ( X [ y <= 0 , 0 ], X [ y <= 0 , 1 ], "r."...scikit-learn.org/stable/auto_examples/gaussian_process/plot_gpc_isoprobability.html -
Permutation Importance vs Random Forest Feature...
unknown_value =- 1 , encoded_missing_value =- 1 ) numerical_pipe...'use_encoded_value' unknown_value -1 encoded_missing_value -1 min_frequency None...scikit-learn.org/stable/auto_examples/inspection/plot_permutation_importance.html -
r_regression — scikit-learn 1.7.0 documentation
Added in version 1.1. Returns : correlation_coefficient...User Guide . Added in version 1.0. Parameters : X {array-like,...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.r_regression.html -
sklearn.preprocessing — scikit-learn 1.7.0 docu...
Scale each feature to the [-1, 1] range without breaking the...data (set feature values to 0 or 1) according to a threshold. FunctionTransformer...scikit-learn.org/stable/api/sklearn.preprocessing.html -
Normal, Ledoit-Wolf and OAS Linear Discriminant...
n_features_range = range ( 1 , n_features_max + 1 , step ) for n_features...n_samples = n_samples , n_features = 1 , centers = [[ - 2 ], [ 2 ]])...scikit-learn.org/stable/auto_examples/classification/plot_lda.html -
Post-hoc tuning the cut-off point of decision f...
0001 C 1.0 fit_intercept True intercept_scaling 1 class_weight...tuned_model_coef . boxplot ( ax = ax [ 1 ]) ax [ 1 ] . set_title ( "Tuned model"...scikit-learn.org/stable/auto_examples/model_selection/plot_tuned_decision_threshold.html