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make_sparse_spd_matrix — scikit-learn 1.5.2 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 -
ShuffleSplit — scikit-learn 1.5.2 documentation
array ([ 1 , 2 , 1 , 2 , 1 , 2 ]) >>> rs = ShuffleSplit...Train: index=[1 3 0 4] Test: index=[5 2] Fold 1: Train: index=[4...scikit-learn.org/stable/modules/generated/sklearn.model_selection.ShuffleSplit.html -
homogeneity_score — scikit-learn 1.5.2 document...
1 , 1 ], [ 1 , 1 , 0 , 0 ]) np.float64(1.0) Non-perfect...homogeneity_score ([ 0 , 0 , 1 , 1 ], [ 0 , 0 , 1 , 2 ])) 1.000000 >>> print...scikit-learn.org/stable/modules/generated/sklearn.metrics.homogeneity_score.html -
SparseCoder — scikit-learn 1.5.2 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.SparseCoder.html -
VotingClassifier — scikit-learn 1.5.2 documenta...
([[ - 1 , - 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2...2 , 1 ], [ 3 , 2 ]]) >>> y = np . array ([ 1 , 1 , 1 , 2 , 2...scikit-learn.org/stable/modules/generated/sklearn.ensemble.VotingClassifier.html -
StratifiedShuffleSplit — scikit-learn 1.5.2 doc...
array ([[ 1 , 2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ], [ 1 , 2 ], [...np . array ([ 0 , 0 , 0 , 1 , 1 , 1 ]) >>> sss = StratifiedShuffleSpl...scikit-learn.org/stable/modules/generated/sklearn.model_selection.StratifiedShuffleSplit.html -
PowerTransformer — scikit-learn 1.5.2 documenta...
[[-1.316... -0.707...] [ 0.209... -0.707...] [ 1.106... 1.414...]]...X_trans * lambda_ + 1 ) ** ( 1 / lambda_ ) - 1 elif X < 0 and lambda_...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.PowerTransformer.html -
hinge_loss — scikit-learn 1.5.2 documentation
[ 1 ]] >>> y = [ - 1 , 1 ] >>> est = svm . LinearSVC...0.09...]) >>> hinge_loss ([ - 1 , 1 , 1 ], pred_decision ) np.float64(0.30...)...scikit-learn.org/stable/modules/generated/sklearn.metrics.hinge_loss.html -
OrdinalEncoder — scikit-learn 1.5.2 documentation
inverse_transform ([[ 1 , 0 ], [ 0 , 1 ]]) array([['Male', 1], ['Female',... =- 1 ) . fit_transform ( X ) array([[ 1., 0.], [ 0., 1.], [...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OrdinalEncoder.html -
ClassifierMixin — scikit-learn 1.5.2 documentation
predict ( X ) array([1, 1, 1]) >>> estimator . score ( X...MyEstimator ( param = 1 ) >>> X = np . array ([[ 1 , 2 ], [ 2 , 3 ],...scikit-learn.org/stable/modules/generated/sklearn.base.ClassifierMixin.html