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CountVectorizer — scikit-learn 1.8.0 docu...
[[0 1 1 1 0 0 1 0 1] [0 2 0 1 0 1 1 0 1] [1 0 0 1 1 0 1 1 1] [0...[[0 0 1 1 0 0 1 0 0 0 0 1 0] [0 1 0 1 0 1 0 1 0 0 1 0 0] [1 0 0...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.text.CountVectorizer.html -
LocalOutlierFactor — scikit-learn 1.8.0 d...
() array([[1., 0., 1.], [0., 1., 1.], [1., 0., 1.]]) predict...fit_predict ( X ) array([ 1, 1, -1, 1]) >>> clf . neg...scikit-learn.org/stable/modules/generated/sklearn.neighbors.LocalOutlierFactor.html -
empirical_covariance — scikit-learn 1.8.0...
>>> X = [[ 1 , 1 , 1 ],[ 1 , 1 , 1 ],[ 1 , 1 , 1 ], ... [ 0 ,...scikit-learn.org/stable/modules/generated/sklearn.covariance.empirical_covariance.html -
contingency_matrix — scikit-learn 1.8.0 d...
labels_pred ) array([[1, 1, 0], [0, 1, 1], [1, 0, 1]]) On this page...0 , 0 , 1 , 1 , 2 , 2 ] >>> labels_pred = [ 1 , 0 , 2...scikit-learn.org/stable/modules/generated/sklearn.metrics.cluster.contingency_matrix.html -
resample — scikit-learn 1.8.0 documentation
1 , 1 , 1 , 1 , 1 , 1 , 1 ] >>> resample...... random_state = 0 ) [1, 1, 1, 0, 1] On this page This Page...scikit-learn.org/stable/modules/generated/sklearn.utils.resample.html -
ShuffleSplit — scikit-learn 1.8.0 documen...
array ([ 1 , 2 , 1 , 2 , 1 , 2 ]) >>> rs...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 -
cosine_distances — scikit-learn 1.8.0 doc...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0...cosine_distances ( X , Y ) array([[1. , 1. ], [0.422, 0.183]]) On this...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.cosine_distances.html -
NearestNeighbors — scikit-learn 1.8.0 doc...
() 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 -
LabelBinarizer — scikit-learn 1.8.0 docum...
array([[1, 0, 0], [0, 1, 0], [0, 0, 1], [0, 1, 0]]) fit ( y )...fit ( np . array ([[ 0 , 1 , 1 ], [ 1 , 0 , 0 ]])) LabelBinarizer()...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.LabelBinarizer.html -
compute_optics_graph — scikit-learn 1.8.0...
1.41, 1.41, 1. , 1. , 4.12]) >>>...min_samples int > 1 or float between 0 and 1 The number of samples...scikit-learn.org/stable/modules/generated/sklearn.cluster.compute_optics_graph.html