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type_of_target — scikit-learn 1.7.2 docum...
>>> type_of_target ([ 1 , - 1 , - 1 , 1 ]) 'binary' >>>...type_of_target ( np . array ([[ 0 , 1 ], [ 1 , 1 ]])) 'multilabel-indicator'...scikit-learn.org/stable/modules/generated/sklearn.utils.multiclass.type_of_target.html -
sparse_encode — scikit-learn 1.7.2 docume...
1 , 0 ], ... [ - 1 , - 1 , 2 ], ... [ 1 , 1 , 1 ], ......>>> X = np . array ([[ - 1 , - 1 , - 1 ], [ 0 , 0 , 3 ]]) >>>...scikit-learn.org/stable/modules/generated/sklearn.decomposition.sparse_encode.html -
fowlkes_mallows_score — scikit-learn 1.7....
1 , 1 ], [ 0 , 0 , 1 , 1 ]) 1.0 >>> ...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 -
Elastic Common Schema (ECS) Reference [1.12] | ...
1 8.0 1.12 1.11 1.10 1.9 1.8 1.7 1.6 1.5 1.4 1.3 1.2 1.1 1.0...Schema (ECS) Reference: 8.17 1.12 other versions other versions:...www.elastic.co/guide/en/ecs/1.12/index.html -
MultiTaskLassoCV — scikit-learn 1.7.2 doc...
since version 1.7: n_alphas was deprecated in 1.7 and will be...since version 1.7: alphas=None was deprecated in 1.7 and will be...scikit-learn.org/stable/modules/generated/sklearn.linear_model.MultiTaskLassoCV.html -
PredefinedSplit — scikit-learn 1.7.2 docu...
1 , 1 ]) >>> test_fold = [ 0 , 1 , - 1 , 1 ] >>>...PredefinedSplit(test_fold=array([ 0, 1, -1, 1])) >>> for i , (...scikit-learn.org/stable/modules/generated/sklearn.model_selection.PredefinedSplit.html -
polynomial_kernel — scikit-learn 1.7.2 do...
[ 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 -
KDTree — scikit-learn 1.7.2 documentation
query ( X [: 1 ], k = 3 ) >>> print...indices of 3 closest neighbors [0 3 1] >>> print ( dist ) #...scikit-learn.org/stable/modules/generated/sklearn.neighbors.KDTree.html -
homogeneity_completeness_v_measure — scik...
1 , 1 , 2 , 2 ], [ 0 , 0 , 1 , 2 , 2 , 2 ] >>>...float Score between 0.0 and 1.0. 1.0 stands for perfectly homogeneous...scikit-learn.org/stable/modules/generated/sklearn.metrics.homogeneity_completeness_v_measure.html -
paired_manhattan_distances — scikit-learn...
array ([[ 1 , 1 , 0 ], [ 0 , 1 , 0 ], [ 0 , 0 , 1 ]]) >>>...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