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grid_search.rst.txt
+--------- | 3 * 2 = 6 | 70 // 2 = 35 | +--------- | 6 * 2 = 12 | 35...35 // 2 = 17 | +--------- | 12 * 2 = 24 | 17 // 2 = 8 | +---------...scikit-learn.org/stable/_sources/modules/grid_search.rst.txt -
ShuffleSplit — scikit-learn 1.8.0 documentation
2 , 1 , 2 , 1 , 2 ]) >>> rs = ShuffleSplit...Test: index=[5 2] Fold 1: Train: index=[4 0 2 5] Test: index=[1...scikit-learn.org/stable/modules/generated/sklearn.model_selection.ShuffleSplit.html -
confusion_matrix — scikit-learn 1.8.0 documenta...
= [ 2 , 0 , 2 , 2 , 0 , 1 ] >>> y_pred = [ 0 , 0 , 2 , 2 , 0...0 , 2 ] >>> confusion_matrix ( y_true , y_pred ) array([[2, 0,...scikit-learn.org/stable/modules/generated/sklearn.metrics.confusion_matrix.html -
Multilabel classification — scikit-learn 1.8.0 ...
subplot ( 2 , 2 , subplot ) plt . title ( title..."none" , linewidths = 2 , label = "Class 2" , ) plot_hyperplane...scikit-learn.org/stable/auto_examples/miscellaneous/plot_multilabel.html -
LeavePOut — scikit-learn 1.8.0 documentation
3] Test: index=[0 2] Fold 2: Train: index=[1 2] Test: index=[0...array ([ 1 , 2 , 3 , 4 ]) >>> lpo = LeavePOut ( 2 ) >>> lpo ....scikit-learn.org/stable/modules/generated/sklearn.model_selection.LeavePOut.html -
preprocessing.rst.txt
2. , 1. , 0.1], [4.4, 2.2, 1.1, 0.1], [4.4, 2.2, 1.2, 0.1],...4.1, 6.7, 2.5], [7.7, 4.2, 6.7, 2.5], [7.9, 4.4, 6.9, 2.5]]) Thus...scikit-learn.org/stable/_sources/modules/preprocessing.rst.txt -
KNeighborsTransformer — scikit-learn 1.8.0 docu...
array([[2]])) As you can see, it returns [[0.5]], and [[2]], which..., metric = 'minkowski' , p = 2 , metric_params = None , n_jobs...scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsTransformer.html -
3.4. Metrics and scoring: quantifying the quali...
y_true = [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2 ] >>> r2_score...y_true = [ - 2 , - 2 , - 2 ] >>> y_pred = [ - 2 , - 2 , - 2 + 1e-8...scikit-learn.org/stable/modules/model_evaluation.html -
LeavePGroupsOut — scikit-learn 1.8.0 documentation
group=[2] Test: index=[0 2], group=[1 3] Fold 2: Train: index=[0],...array ([ 1 , 2 , 1 ]) >>> groups = np . array ([ 1 , 2 , 3 ]) >>>...scikit-learn.org/stable/modules/generated/sklearn.model_selection.LeavePGroupsOut.html -
RegressorChain — scikit-learn 1.8.0 documentation
2 ], [ 1 , 1 ], [ 2 , 0 ]] >>> chain = RegressorChain...predict ( X ) array([[0., 2.], [1., 1.], [2., 0.]]) fit ( X , Y ,...scikit-learn.org/stable/modules/generated/sklearn.multioutput.RegressorChain.html