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LabelBinarizer — scikit-learn 1.8.0 documentation
array([[1, 0, 0], [0, 1, 0], [0, 0, 1], [0, 1, 0]]) fit ( y ) [source]...array([1, 2, 4, 6]) >>> lb . transform ([ 1 , 6 ]) array([[1, 0,...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelBinarizer.html -
polynomial_kernel — scikit-learn 1.8.0 document...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>..., degree = 2 ) array([[1. , 1. ], [1.77, 2.77]]) On this page...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.polynomial_kernel.html -
PredefinedSplit — scikit-learn 1.8.0 documentation
1 , 1 ]) >>> test_fold = [ 0 , 1 , - 1 , 1 ] >>> ps...PredefinedSplit(test_fold=array([ 0, 1, -1, 1])) >>> for i , ( train_index...scikit-learn.org/stable/modules/generated/sklearn.model_selection.PredefinedSplit.html -
paired_manhattan_distances — scikit-learn 1.8.0...
array ([[ 1 , 1 , 0 ], [ 0 , 1 , 0 ], [ 0 , 0 , 1 ]]) >>> Y =...calculated between (X[0], Y[0]), (X[1], Y[1]), …, (X[n_samples], Y[n_samples])....scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.paired_manhattan_distances.html -
fowlkes_mallows_score — scikit-learn 1.8.0 docu...
1 , 1 ], [ 0 , 0 , 1 , 1 ]) 1.0 >>> fowlkes_mallows_score...fowlkes_mallows_score ([ 0 , 0 , 1 , 1 ], [ 1 , 1 , 0 , 0 ]) 1.0 If classes members...scikit-learn.org/stable/modules/generated/sklearn.metrics.fowlkes_mallows_score.html -
minmax_scale — scikit-learn 1.8.0 documentation
1 , 2 ], [ - 1 , 0 , 1 ]] >>> minmax_scale...independently array([[0., 1., 1.], [1., 0., 0.]]) >>> minmax_scale...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.minmax_scale.html -
paired_euclidean_distances — scikit-learn 1.8.0...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>...paired_euclidean_distances ( X , Y ) array([1., 1.]) On this page This Page...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.paired_euclidean_distances.html -
make_sparse_spd_matrix — scikit-learn 1.8.0 doc...
array([[1., 0., 0., 0.], [0., 1., 0., 0.], [0., 0., 1., 0.], [0.,...elements all 1. smallest_coef float, default=0.1 The value of...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_sparse_spd_matrix.html -
confusion_matrix — scikit-learn 1.8.0 documenta...
1 , 0 , 1 ], [ 1 , 1 , 1 , 0 ]) . ravel ()...) array([[2, 0, 0], [0, 0, 1], [1, 0, 2]]) >>> y_true = [ "cat"...scikit-learn.org/stable/modules/generated/sklearn.metrics.confusion_matrix.html -
f1_score — scikit-learn 1.8.0 documentation
[ 1 , 1 , 1 ], [ 0 , 1 , 1 ]] >>> y_pred = [[...[[ 0 , 0 , 0 ], [ 1 , 1 , 1 ], [ 1 , 1 , 0 ]] >>> f1_score ( y_true...scikit-learn.org/stable/modules/generated/sklearn.metrics.f1_score.html