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make_moons — scikit-learn 1.5.2 documentation
) The integer labels (0 or 1) for class membership of each...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_moons.html -
2.3. Clustering — scikit-learn 1.5.2 documentation
1 , 1 , 1 ] >>> labels_pred = [ 0 , 0 , 1 , 1 , 2 , 2...0 , 0 , 1 , 1 , 1 ] >>> labels_pred = [ 0 , 0 , 1 , 1 , 2 , 2...scikit-learn.org/stable/modules/clustering.html -
StratifiedGroupKFold — scikit-learn 1.5.2 docum...
1 , 1 , 1 , 1 , 1 , 1 , 0 , 0 , 0 , 0 , 0...Train: index=[ 0 1 2 3 7 8 9 10 11 15 16] group=[1 1 2 2 4 5 5 5 5...scikit-learn.org/stable/modules/generated/sklearn.model_selection.StratifiedGroupKFold.html -
6.3. Preprocessing data — scikit-learn 1.5.2 do...
1. , 0.1], [4.4, 2.2, 1.1, 0.1], [4.4, 2.2, 1.2, 0.1], ...,...array([[1., 0., 0., 1., 0., 1.], [0., 1., 1., 0., 0., 1.]]) By...scikit-learn.org/stable/modules/preprocessing.html -
6.2. Feature extraction — scikit-learn 1.5.2 do...
array([[1, 1, 1, 0, 1, 1, 1, 0], [1, 1, 0, 1, 1, 1, 0, 1]]) In...array([[0, 1, 1, 1, 0, 0, 1, 0, 1], [0, 1, 0, 1, 0, 2, 1, 0, 1], [1,...scikit-learn.org/stable/modules/feature_extraction.html -
f_classif — scikit-learn 1.5.2 documentation
1...e-27, 4.0...e-01, 1.9...e-01, 3.3...e-01,...= 2 , n_clusters_per_class = 1 , ... shuffle = False , random_state...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.f_classif.html -
brier_score_loss — scikit-learn 1.5.2 documenta...
y_true in {-1, 1} or {0, 1}, pos_label defaults to 1; else if y_true...0 or all -1, in which case pos_label defaults to 1. Read more...scikit-learn.org/stable/modules/generated/sklearn.metrics.brier_score_loss.html -
OneHotEncoder — scikit-learn 1.5.2 documentation
scikit-learn 1.1 Release Highlights for scikit-learn 1.1 Release Highlights...'Female' , 1 ], [ 'Male' , 4 ]]) . toarray () array([[1., 0., 1., 0.,...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OneHotEncoder.html -
average_precision_score — scikit-learn 1.5.2 do...
1 , 1 ]) >>> y_scores = np . array ([ 0.1 , 0.4 , 0.35..., 0.1 ], ... [ 0.4 , 0.3 , 0.3 ], ... [ 0.1 , 0.8 , 0.1 ], ......scikit-learn.org/stable/modules/generated/sklearn.metrics.average_precision_score.html -
make_gaussian_quantiles — scikit-learn 1.5.2 do...
dataset is from Zhu et al [1]. References [ 1 ] Zhu, H. Zou, S. Rosset,...es ( * , mean = None , cov = 1.0 , n_samples = 100 , n_features...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_gaussian_quantiles.html