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VarianceThreshold — scikit-learn 1.8.0 document...
1 , 4 , 3 ], [ 0 , 1 , 1 , 3 ]] >>> selector...fit_transform ( X ) array([[2, 0], [1, 4], [1, 1]]) fit ( X , y = None )...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.VarianceThreshold.html -
MultiLabelBinarizer — scikit-learn 1.8.0 docume...
fit_transform ([( 1 , 2 ), ( 3 ,)]) array([[1, 1, 0], [0, 0, 1]]) >>> mlb...{ 'comedy' }]) array([[0, 1, 1], [1, 0, 0]]) >>> list ( mlb ....scikit-learn.org/stable/modules/generated/sklearn.preprocessing.MultiLabelBinarizer.html -
DummyClassifier — scikit-learn 1.8.0 documentation
([ - 1 , 1 , 1 , 1 ]) >>> y = np . array ([ 0 , 1 , 1 , 1 ]) >>>...dummy_clf . predict ( X ) array([1, 1, 1, 1]) >>> dummy_clf . score (...scikit-learn.org/stable/modules/generated/sklearn.dummy.DummyClassifier.html -
DBSCAN — scikit-learn 1.8.0 documentation
1, 1, -1]) >>> clustering DBSCAN(eps=3,...means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html -
MeanShift — scikit-learn 1.8.0 documentation
array ([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7...clustering . labels_ array([1, 1, 1, 0, 0, 0]) >>> clustering ....scikit-learn.org/stable/modules/generated/sklearn.cluster.MeanShift.html -
ledoit_wolf_shrinkage — scikit-learn 1.8.0 docu...
regularized (shrunk) covariance is: (1 - shrinkage) * cov + shrinkage...scikit-learn.org/stable/modules/generated/sklearn.covariance.ledoit_wolf_shrinkage.html -
Binarizer — scikit-learn 1.8.0 documentation
( X ) array([[1., 0., 1.], [1., 0., 0.], [0., 1., 0.]]) fit (...= [[ 1. , - 1. , 2. ], ... [ 2. , 0. , 0. ], ... [ 0. , 1. , -...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.Binarizer.html -
balanced_accuracy_score — scikit-learn 1.8.0 do...
1 , 0 , 0 , 1 , 0 ] >>> y_pred = [ 0 , 1 , 0 , 0 ,...each class. The best value is 1 and the worst value is 0 when...scikit-learn.org/stable/modules/generated/sklearn.metrics.balanced_accuracy_score.html -
RBF — scikit-learn 1.8.0 documentation
return_X_y = True ) >>> kernel = 1.0 * RBF ( 1.0 ) >>> gpc = GaussianProcessClass...ernels. RBF ( length_scale = 1.0 , length_scale_bounds = (1e-05,...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.RBF.html -
MultiOutputRegressor — scikit-learn 1.8.0...
means 1 unless in a joblib.parallel_backend context. -1 means...X [[ 0 ]]) array([[176, 35.1, 57.1]]) fit ( X , y , sample_weight...scikit-learn.org/stable/modules/generated/sklearn.multioutput.MultiOutputRegressor.html