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normalize — scikit-learn 1.8.0 documentation
1 , 2 ], [ - 1 , 0 , 1 ]] >>> normalize...if axis is 0). axis {0, 1}, default=1 Define axis used to normalize...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.normalize.html -
RepeatedStratifiedKFold — scikit-learn 1....
array ([[ 1 , 2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ]])...>>> y = np . array ([ 0 , 0 , 1 , 1 ]) >>> rskf = RepeatedStratifiedKF...scikit-learn.org/stable/modules/generated/sklearn.model_selection.RepeatedStratifiedKFold.html -
ward_tree — scikit-learn 1.8.0 documentation
array ([[ 1 , 2 ], [ 1 , 4 ], [ 1 , 0 ], ... [ 4 , 2...children ndarray of shape (n_nodes-1, 2) The children of each non-leaf...scikit-learn.org/stable/modules/generated/sklearn.cluster.ward_tree.html -
pairwise_kernels — scikit-learn 1.8.0 doc...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0...means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.pairwise_kernels.html -
pairwise_distances — scikit-learn 1.8.0 d...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0...deprecated from SciPy 1.9 and will be removed in SciPy 1.11. Note 'matching'...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise_distances.html -
estimate_bandwidth — scikit-learn 1.8.0 d...
array ([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7...means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn.org/stable/modules/generated/sklearn.cluster.estimate_bandwidth.html -
johnson_lindenstrauss_min_dim — scikit-le...
by: (1 - eps) ||u - v||^2 < ||p(u) - p(v)||^2 < (1 + eps)...]0, 1[ and p is a projection by a random Gaussian N(0, 1) matrix...scikit-learn.org/stable/modules/generated/sklearn.random_projection.johnson_lindenstrauss_min_dim... -
train_test_split — scikit-learn 1.8.0 doc...
1 3.5 1.4 0.2 1 4.9 3.0 1.4 0.2 2 4.7 3.2 1.3 0.2 3 4.6...4.2 1.3 105 7.6 3.0 6.6 2.1 66 5.6 3.0 4.5 1.5 0 5.1 3.5 1.4 0.2...scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html -
SpectralBiclustering — scikit-learn 1.8.0...
array ([[ 1 , 1 ], [ 2 , 1 ], [ 1 , 0 ], ... [ 4 , 7...clustering . row_labels_ array([1, 1, 1, 0, 0, 0], dtype=int32) >>>...scikit-learn.org/stable/modules/generated/sklearn.cluster.SpectralBiclustering.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