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6.1. Pipelines and composite estimators — sciki...
1.1.1. Usage # 6.1.1.1.1. Build a pipeline...0, 0, 0, 1, 0, 1, 0, 0, 1, 1, 1, 0], [0, 1, 0, 0, 1, 0, 0, 0,...scikit-learn.org/stable/modules/compose.html -
Release Highlights for scikit-learn 1.5 — sciki...
array([[-1.1, 1.1, 1.1], [ 3.9, -1.2, 1.1], [ 0.1, 1.3, 1.1], [-0.1,...[-0.1, -1.4, -1.4], [-4.9, 1.5, -1.5], [ 0.1, 1.6, 1.6]]) Pairwise...scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_5_0.html -
fetch_openml — scikit-learn 1.5.0 documentation
scikit-learn 1.1 Release Highlights for scikit-learn 1.1 Release Highlights...Added in version 1.2. Changed in version 1.4: The default value...scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_openml.html -
brier_score_loss — scikit-learn 1.5.0 documenta...
y_true in {-1, 1} or {0, 1}, pos_label defaults to 1; else if y_true...0 or all -1, in which case pos_label defaults to 1. Read more...scikit-learn.org/stable/modules/generated/sklearn.metrics.brier_score_loss.html -
2.3. Clustering — scikit-learn 1.5.0 documentation
1 , 1 , 1 ] >>> labels_pred = [ 0 , 0 , 1 , 1 , 2 , 2...0 , 0 , 1 , 1 , 1 ] >>> labels_pred = [ 0 , 0 , 1 , 1 , 2 , 2...scikit-learn.org/stable/modules/clustering.html -
average_precision_score — scikit-learn 1.5.0 do...
1 , 1 ]) >>> y_scores = np . array ([ 0.1 , 0.4 , 0.35..., 0.1 ], ... [ 0.4 , 0.3 , 0.3 ], ... [ 0.1 , 0.8 , 0.1 ], ......scikit-learn.org/stable/modules/generated/sklearn.metrics.average_precision_score.html -
pairwise_distances_argmin — scikit-learn 1.5.0 ...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>...deprecated from SciPy 1.9 and will be removed in SciPy 1.11. Note 'matching'...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise_distances_argmin.html -
roc_auc_score — scikit-learn 1.5.0 documentation
classes_[1] and thus estimator.predict_proba(X, y)[:, 1] . The...it is upper bounded by 1. References [ 1 ] Wikipedia entry for...scikit-learn.org/stable/modules/generated/sklearn.metrics.roc_auc_score.html -
f_classif — scikit-learn 1.5.0 documentation
1...e-27, 4.0...e-01, 1.9...e-01, 3.3...e-01,...= 2 , n_clusters_per_class = 1 , ... shuffle = False , random_state...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.f_classif.html -
mean_pinball_loss — scikit-learn 1.5.0 document...
1 ) 0.03... >>> mean_pinball_loss ( y_true , [ 1 , 2 ,...scikit-learn 1.0 Release Highlights for scikit-learn 1.0 Features...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_pinball_loss.html