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completeness_score — scikit-learn 1.8.0 documen...
1 , 1 ], [ 1 , 1 , 0 , 0 ]) 1.0 Non-perfect labelings...completeness_score ([ 0 , 0 , 1 , 1 ], [ 0 , 1 , 0 , 1 ])) 0.0 >>> print...scikit-learn.org/stable/modules/generated/sklearn.metrics.completeness_score.html -
sparse_encode — scikit-learn 1.8.0 documentation
1 , 0 ], ... [ - 1 , - 1 , 2 ], ... [ 1 , 1 , 1 ], ......>>> X = np . array ([[ - 1 , - 1 , - 1 ], [ 0 , 0 , 3 ]]) >>> dictionary...scikit-learn.org/stable/modules/generated/sklearn.decomposition.sparse_encode.html -
precision_score — scikit-learn 1.8.0 documentation
[ 1 , 1 , 1 ], [ 0 , 1 , 1 ]] >>> y_pred = [[...[[ 0 , 0 , 0 ], [ 1 , 1 , 1 ], [ 1 , 1 , 0 ]] >>> precision_score...scikit-learn.org/stable/modules/generated/sklearn.metrics.precision_score.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 -
type_of_target — scikit-learn 1.8.0 documentation
1 , 0.6 ]) 'continuous' >>> type_of_target ([ 1 , - 1 , -...type_of_target ( np . array ([[ 0 , 1 ], [ 1 , 1 ]])) 'multilabel-indicator'...scikit-learn.org/stable/modules/generated/sklearn.utils.multiclass.type_of_target.html -
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 -
NearestNeighbors — scikit-learn 1.8.0 documenta...
() array([[1., 0., 1.], [0., 1., 1.], [1., 0., 1.]]) radius_neighbors...() array([[1., 0., 1.], [0., 1., 0.], [1., 0., 1.]]) set_params...scikit-learn.org/stable/modules/generated/sklearn.neighbors.NearestNeighbors.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 -
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