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OrdinalEncoder — scikit-learn 1.8.0 docum...
inverse_transform ([[ 1 , 0 ], [ 0 , 1 ]]) array([['Male', 1], ['Female',... =- 1 ) . fit_transform ( X ) array([[ 1., 0.], [ 0., 1.], [...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OrdinalEncoder.html -
Pipeline ANOVA SVM — scikit-learn 1.8.0 d...
versionchanged:: 1.3 The `"auto"` option is added in version 1.3 and will...intercept term: `[x_1, ..., x_n, 1]`, where 1 corresponds to the intercept....scikit-learn.org/stable/auto_examples/feature_selection/plot_feature_selection_pipeline.html -
sort_graph_by_row_values — scikit-learn 1...
1. ], ... [ 3. , 0. , 2. ], ... [ 1. , 2. , 0. ]])...>>> X . data array([3., 1., 3., 2., 1., 2.]) >>> X_ =...scikit-learn.org/stable/modules/generated/sklearn.neighbors.sort_graph_by_row_values.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 -
BallTree — scikit-learn 1.8.0 documentation
query ( X [: 1 ], k = 3 ) >>> print...indices of 3 closest neighbors [0 3 1] >>> print ( dist ) #...scikit-learn.org/stable/modules/generated/sklearn.neighbors.BallTree.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 -
Metadata Routing — scikit-learn 1.8.0 doc...
array([1., 1., 1.]) Routing Meta-Estimator...ExampleClassifier. array([1., 1., 1.]) Deprecation / Default Value...scikit-learn.org/stable/auto_examples/miscellaneous/plot_metadata_routing.html -
Compare cross decomposition methods — sci...
[[ 1. 0.48 -0.01 0. ] [ 0.48 1. -0.01 0. ] [-0.01 -0.01 1. 0.49]...0. 0.49 1. ]] Corr(Y) [[ 1. 0.47 0.03 0.05] [ 0.47 1. 0.03 -0.01]...scikit-learn.org/stable/auto_examples/cross_decomposition/plot_compare_cross_decomposition.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 -
dbscan — scikit-learn 1.8.0 documentation
1, 2, 3, 4]) >>> labels array([ 0, 0, 0, 1, 1, -1])...means 1 unless in a joblib.parallel_backend context. -1 means...scikit-learn.org/stable/modules/generated/dbscan-function.html