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LocalOutlierFactor — scikit-learn 1.8.0 documen...
() array([[1., 0., 1.], [0., 1., 1.], [1., 0., 1.]]) predict...fit_predict ( X ) array([ 1, 1, -1, 1]) >>> clf . negative_outlier_factor_...scikit-learn.org/stable/modules/generated/sklearn.neighbors.LocalOutlierFactor.html -
empirical_covariance — scikit-learn 1.8.0 docum...
>>> 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 documen...
labels_pred ) array([[1, 1, 0], [0, 1, 1], [1, 0, 1]]) On this page..., 0 , 1 , 1 , 2 , 2 ] >>> labels_pred = [ 1 , 0 , 2 , 1 , 0 ,...scikit-learn.org/stable/modules/generated/sklearn.metrics.cluster.contingency_matrix.html -
ShuffleSplit — scikit-learn 1.8.0 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 -
VotingClassifier — scikit-learn 1.8.0 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 -
cosine_distances — scikit-learn 1.8.0 documenta...
[ 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 -
MultinomialNB — scikit-learn 1.8.0 documentation
Added in version 1.2. Changed in version 1.4: The default value... MultinomialNB ( * , alpha = 1.0 , force_alpha = True , fit_prior...scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.MultinomialNB.html -
RegressorChain — scikit-learn 1.8.0 documentation
= [[ 1 , 0 ], [ 0 , 1 ], [ 1 , 1 ]], [[ 0 , 2 ], [ 1 , 1 ], [...order = [ 0 , 1 , 2 , ... , Y . shape [ 1 ] - 1 ] The order of...scikit-learn.org/stable/modules/generated/sklearn.multioutput.RegressorChain.html -
cluster_optics_xi — scikit-learn 1.8.0 document...
1, 1, 1]) >>> clusters array([[0, 2],...min_samples int > 1 or float between 0 and 1 The same as the min_samples...scikit-learn.org/stable/modules/generated/sklearn.cluster.cluster_optics_xi.html -
compute_optics_graph — scikit-learn 1.8.0 docum...
1. , 1. , 4.12]) >>> reachability array([ inf, 3.16, 1.41,...1.41, 4.12, 1. , 5. ]) >>> predecessor array([-1, 0, 1, 5, 3, 2])...scikit-learn.org/stable/modules/generated/sklearn.cluster.compute_optics_graph.html