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ParameterSampler — scikit-learn 1.6.1 documenta...
'a' : 1 }, ... { 'b' : 0.923223 , 'a' : 1 }, ... { 'b' : 1.878964...0 ) >>> param_grid = { 'a' :[ 1 , 2 ], 'b' : expon ()} >>> param_list...scikit-learn.org/stable/modules/generated/sklearn.model_selection.ParameterSampler.html -
Label Propagation digits active learning — scik...
support 0 1.00 1.00 1.00 22 1 0.85 1.00 0.92 22 2 1.00 1.00 1.00 28...support 0 1.00 1.00 1.00 22 1 0.85 1.00 0.92 22 2 1.00 1.00 1.00 27...scikit-learn.org/stable/auto_examples/semi_supervised/plot_label_propagation_digits_active_learni... -
binarize — scikit-learn 1.6.1 documentation
1., 0.], [1., 0., 0.]]) On this page...are replaced by 0, above it by 1. Threshold may not be less than...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.binarize.html -
sparse_encode — scikit-learn 1.6.1 documentation
1 , 0 ], ... [ - 1 , - 1 , 2 ], ... [ 1 , 1 , 1 ], ......>>> X = np . array ([[ - 1 , - 1 , - 1 ], [ 0 , 0 , 3 ]]) >>> dictionary...scikit-learn.org/stable/modules/generated/sklearn.decomposition.sparse_encode.html -
Decision Tree Regression — scikit-learn 1.6.1 d...
scatter ( y_1 [:, 0 ], y_1 [:, 1 ], c = "cornflowerblue"...RandomState ( 1 ) X = np . sort ( 5 * rng . rand ( 80 , 1 ), axis =...scikit-learn.org/stable/auto_examples/tree/plot_tree_regression.html -
Version 0.23 — scikit-learn 1.6.1 documentation
arguments n_classes < 1 OR length < 1 . #16006 by Rushabh Vasani...Bruno Charron . Version 0.23.1 # May 18 2020 Changelog # sklearn.cluster...scikit-learn.org/stable/whats_new/v0.23.html -
polynomial_kernel — scikit-learn 1.6.1 document...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>..., degree = 2 ) array([[1. , 1. ], [1.77..., 2.77...]]) On this...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.polynomial_kernel.html -
multilabel_confusion_matrix — scikit-learn 1.6....
array([[[1, 0], [0, 1]], [[1, 0], [0, 1]], [[0, 1], [1, 0]]]) Multiclass...array([[[3, 1], [0, 2]], [[5, 0], [1, 0]], [[2, 1], [1, 2]]]) On...scikit-learn.org/stable/modules/generated/sklearn.metrics.multilabel_confusion_matrix.html -
Lagged features for time series forecasting — s...
1 ± 1.1" "19.9 ± 1.6" "22.7 ± 3.1" "quantile 5"..."39.9 ± 3.2" "17.1 ± 1.1" "19.9 ± 1.6" "22.7 ± 3.1" "quantile 95"...scikit-learn.org/stable/auto_examples/applications/plot_time_series_lagged_features.html -
OrdinalEncoder — scikit-learn 1.6.1 documentation
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