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shuffle — scikit-learn 1.8.0 documentation
[2., 1.], [1., 0.]]) >>> y array([2, 1, 0]) >>>...= np . array ([[ 1. , 0. ], [ 2. , 1. ], [ 0. , 0. ]]) >>>...scikit-learn.org/stable/modules/generated/sklearn.utils.shuffle.html -
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 -
zero_one_loss — scikit-learn 1.8.0 docume...
2 , 3 , 4 ] >>> y_true = [ 2 , 2 , 3 , 4 ]...], [ 1 , 1 ]]), np . ones (( 2 , 2 ))) 0.5 On this page This Page...scikit-learn.org/stable/modules/generated/sklearn.metrics.zero_one_loss.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_classifier_comparison.zip
make_classification( n_features=2, n_redundant=0, n_informative=2, random_state=1,...rng = np.random.RandomState(2) X += 2 * rng.uniform(size=X.shape)...scikit-learn.org/stable/_downloads/ce35bcc69acbd491cf7ac77fa17889d5/plot_classifier_comparison.zip -
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 -
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 -
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