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NuSVR — scikit-learn 1.8.0 documentation
Added in version 1.1. n_support_ ndarray of shape (1,), dtype=int32...(0, 1]. By default 0.5 will be taken. C float, default=1.0 Penalty...scikit-learn.org/stable/modules/generated/sklearn.svm.NuSVR.html -
column_or_1d — scikit-learn 1.8.0 documentation
>>> column_or_1d ([ 1 , 1 ]) array([1, 1]) On this page This...type for y . Added in version 1.2. input_name str, default=”y”...scikit-learn.org/stable/modules/generated/sklearn.utils.validation.column_or_1d.html -
SpectralBiclustering — scikit-learn 1.8.0 docum...
array ([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7...clustering . row_labels_ array([1, 1, 1, 0, 0, 0], dtype=int32) >>>...scikit-learn.org/stable/modules/generated/sklearn.cluster.SpectralBiclustering.html -
train_test_split — scikit-learn 1.8.0 documenta...
1 3.5 1.4 0.2 1 4.9 3.0 1.4 0.2 2 4.7 3.2 1.3 0.2 3 4.6...4.2 1.3 105 7.6 3.0 6.6 2.1 66 5.6 3.0 4.5 1.5 0 5.1 3.5 1.4 0.2...scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html -
LeaveOneOut — scikit-learn 1.8.0 documentation
array ([[ 1 , 2 ], [ 3 , 4 ]]) >>> y = np . array ([ 1 , 2 ]) >>>...0: Train: index=[1] Test: index=[0] Fold 1: Train: index=[0]...scikit-learn.org/stable/modules/generated/sklearn.model_selection.LeaveOneOut.html -
homogeneity_completeness_v_measure — scikit-lea...
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 -
PolynomialCountSketch — scikit-learn 1.8.0 docu...
[ 1 , 1 ], [ 1 , 0 ], [ 0 , 1 ]] >>> y = [ 0 , 0 , 1 , 1 ] >>>...Array with random entries in {+1, -1}, used to represent the 2-wise...scikit-learn.org/stable/modules/generated/sklearn.kernel_approximation.PolynomialCountSketch.html -
AffinityPropagation — scikit-learn 1.8.0 docume...
array ([[ 1 , 2 ], [ 1 , 4 ], [ 1 , 0 ], ... [ 4 , 2.... labels_ array([0, 0, 0, 1, 1, 1]) >>> clustering . predict...scikit-learn.org/stable/modules/generated/sklearn.cluster.AffinityPropagation.html -
ClusterMixin — scikit-learn 1.8.0 documentation
fit_predict ( X ) array([1, 1, 1]) fit_predict ( X , y = None...) ... return self >>> X = [[ 1 , 2 ], [ 2 , 3 ], [ 3 , 4 ]] >>>...scikit-learn.org/stable/modules/generated/sklearn.base.ClusterMixin.html -
TransformerMixin — scikit-learn 1.8.0 documenta...
fit_transform ( X ) array([1, 1, 1]) fit_transform ( X , y = None...__init__ ( self , * , param = 1 ): ... self . param = param ......scikit-learn.org/stable/modules/generated/sklearn.base.TransformerMixin.html