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cluster_optics_xi — scikit-learn 1.8.0 do...
2 ], [ 2 , 5 ], [ 3 , 6 ], ... [ 8...samples (rounded to be at least 2). min_cluster_size int > 1...scikit-learn.org/stable/modules/generated/sklearn.cluster.cluster_optics_xi.html -
One-class SVM with non-linear kernel (RBF) R...
2 ) X_train = np . r_ [ X + 2 , X - 2 ] # Generate...randn ( 20 , 2 ) X_test = np . r_ [ X + 2 , X - 2 ] # Generate...scikit-learn.org/stable/auto_examples/svm/plot_oneclass.html -
plot_release_highlights_1_7_0.rst.txt
id="sk-estimator-id-2" type="checkbox" ><label for="sk-estimator-id-2" clas...#sk-container-id-2 pre { padding: 0; } #sk-container-id-2 input.sk-hidden--visually...scikit-learn.org/stable/_sources/auto_examples/release_highlights/plot_release_highlights_1_7_0.r... -
feature_extraction.rst.txt
2.0986]}{\sqrt{\big(3^2 + 0^2 + 2.0986^2\big)}} = [...(one_image, (2, 2)) >>> patches.shape (9, 2, 2, 3) >>> patches[4,...scikit-learn.org/stable/_sources/modules/feature_extraction.rst.txt -
RegressorChain — scikit-learn 1.8.0 docum...
2 ], [ 1 , 1 ], [ 2 , 0 ]] >>> chain...predict ( X ) array([[0., 2.], [1., 1.], [2., 0.]]) fit ( X , Y ,...scikit-learn.org/stable/modules/generated/sklearn.multioutput.RegressorChain.html -
manhattan_distances — scikit-learn 1.8.0 ...
2 ], [ 3 , 4 ]], [[ 1 , 2 ], [ 0 , 3 ]]) array([[0., 2.],...manhattan_distances ([[ 3 ]], [[ 2 ]]) array([[1.]]) >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.manhattan_distances.html -
Probability Calibration curves — scikit-l...
add_subplot ( gs [: 2 , : 2 ]) calibration_displays = {}...histogram grid_positions = [( 2 , 0 ), ( 2 , 1 ), ( 3 , 0 ), ( 3 ,...scikit-learn.org/stable/auto_examples/calibration/plot_calibration_curve.html -
make_friedman2 — scikit-learn 1.8.0 docum...
0 ] ** 2 + ( X [:, 1 ] * X [:, 2 ] - 1 / ( X [:, 1...[source] # Generate the “Friedman #2” regression problem. This dataset...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_friedman2.html -
roc_curve — scikit-learn 1.8.0 documentation
2 , 2 ]) >>> scores = np...Returns : fpr ndarray of shape (>2,) Increasing false positive rates...scikit-learn.org/stable/modules/generated/sklearn.metrics.roc_curve.html -
VotingClassifier — scikit-learn 1.8.0 doc...
[ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2 , 1 ], [ 3...3 , 2 ]]) >>> y = np . array ([ 1 , 1 , 1 , 2 , 2 , 2...scikit-learn.org/stable/modules/generated/sklearn.ensemble.VotingClassifier.html