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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 -
make_gaussian_quantiles — scikit-learn 1.8.0 do...
int64(2), np.int64(0), np.int64(1), np.int64(0), np.int64(2)] Gallery...n_samples = 100 , n_features = 2 , n_classes = 3 , shuffle = True...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_gaussian_quantiles.html -
Plot randomly generated multilabel dataset — sc...
1500 * p_c ** 2 , color = COLORS . take ([ 1 , 2 , 4 ]), ) ax...means the class is present: 1 2 3 Color Y N N Red N Y N Blue N...scikit-learn.org/stable/auto_examples/datasets/plot_random_multilabel_dataset.html -
GroupKFold — scikit-learn 1.8.0 documentation
Fold 0: Train: index=[2 3], group=[2 2] Test: index=[0 1 4 5],...group=[0 0 3 3] Test: index=[2 3], group=[2 2] get_metadata_routing...scikit-learn.org/stable/modules/generated/sklearn.model_selection.GroupKFold.html -
GroupShuffleSplit — scikit-learn 1.8.0 document...
0: Train: index=[2 3 4 5 6 7], group=[2 2 2 3 3 3] Test: index=[0...3 3 3] Test: index=[2 3 4], group=[2 2 2] get_metadata_routing...scikit-learn.org/stable/modules/generated/sklearn.model_selection.GroupShuffleSplit.html -
One-class SVM with non-linear kernel (RBF) — sc...
2 ) X_train = np . r_ [ X + 2 , X - 2 ] # Generate...randn ( 20 , 2 ) X_test = np . r_ [ X + 2 , X - 2 ] # Generate...scikit-learn.org/stable/auto_examples/svm/plot_oneclass.html -
SQL evaluation framework for accurate query ass...
This results in 2 2 −1 (excluding the empty set)...DESC LIMIT 10 ; Copy code Query 2 SELECT userid, firstname || '...developer.ibm.com/articles/awb-sql-evaluation-llm-generated-sql-queries/ -
cluster_optics_xi — scikit-learn 1.8.0 document...
2 ], [ 2 , 5 ], [ 3 , 6 ], ... [ 8...samples (rounded to be at least 2). min_cluster_size int > 1 or...scikit-learn.org/stable/modules/generated/sklearn.cluster.cluster_optics_xi.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 -
manhattan_distances — scikit-learn 1.8.0 docume...
2 ], [ 3 , 4 ]], [[ 1 , 2 ], [ 0 , 3 ]]) array([[0., 2.],...]], [[ 2 ]]) array([[1.]]) >>> manhattan_distances ([[ 2 ]], [[...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.manhattan_distances.html