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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 -
make_blobs — scikit-learn 1.8.0 documenta...
scikit-learn 1.1 Release Highlights for scikit-learn 1.1 Plot the...>>> y array([0, 0, 1, 0, 2, 2, 2, 1, 1, 0]) >>> X ,...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_blobs.html -
LinearRegression — scikit-learn 1.8.0 doc...
array ([[ 1 , 1 ], [ 1 , 2 ], [ 2 , 2 ], [ 2 ,...means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LinearRegression.html -
make_pipeline — scikit-learn 1.8.0 docume...
scikit-learn 1.1 Release Highlights for scikit-learn 1.1 Release Highlights...scikit-learn 1.0 Release Highlights for scikit-learn 1.0 Release...scikit-learn.org/stable/modules/generated/sklearn.pipeline.make_pipeline.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 -
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 -
lasso_path — scikit-learn 1.8.0 documenta...
array ([[ 1 , 2 , 3.1 ], [ 2.3 , 5.4 , 4.3 ]])...>>> y = np . array ([ 1 , 2 , 3.1 ]) >>> # Use lasso_path...scikit-learn.org/stable/modules/generated/sklearn.linear_model.lasso_path.html -
FeatureHasher — scikit-learn 1.8.0 docume...
-1., 0., -1., 0., 1.], [ 0., 0., 0., -1., 0., -1., 0., 0.],...0.], [ 0., -1., 0., 0., 0., 0., 0., 1.]]) fit ( X = None , y...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.FeatureHasher.html -
MiniBatchSparsePCA — scikit-learn 1.8.0 d...
means 1 unless in a joblib.parallel_backend context. -1 means...tol to 0.0. Added in version 1.1. max_no_improvement int or None,...scikit-learn.org/stable/modules/generated/sklearn.decomposition.MiniBatchSparsePCA.html -
VotingRegressor — scikit-learn 1.8.0 docu...
means 1 unless in a joblib.parallel_backend context. -1 means...>>> X = np . array ([[ 1 , 1 ], [ 2 , 4 ], [ 3 , 9 ], [ 4...scikit-learn.org/stable/modules/generated/sklearn.ensemble.VotingRegressor.html