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mean_pinball_loss — scikit-learn 1.7.2 document...
1 ) 0.03... >>> mean_pinball_loss ( y_true , [ 1 , 2 ,...scikit-learn 1.0 Release Highlights for scikit-learn 1.0 On this...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_pinball_loss.html -
EllipticEnvelope — scikit-learn 1.7.2 documenta...
n_features + 1) / 2 * n_samples . Range is (0, 1). contamination...>>> # predict returns 1 for an inlier and -1 for an outlier >>>...scikit-learn.org/stable/modules/generated/sklearn.covariance.EllipticEnvelope.html -
RFE — scikit-learn 1.7.2 documentation
ranking_ array([1, 1, 1, 1, 1, 6, 4, 3, 2, 5]) decision_function...float, default=1 If greater than or equal to 1, then step corresponds...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.RFE.html -
GroupShuffleSplit — scikit-learn 1.7.2 document...
index=[0 1], group=[1 1] Fold 1: Train: index=[0 1 5 6 7], group=[1...shape = ( 8 , 1 )) >>> groups = np . array ([ 1 , 1 , 2 , 2 , 2...scikit-learn.org/stable/modules/generated/sklearn.model_selection.GroupShuffleSplit.html -
ElasticNetCV — scikit-learn 1.7.2 documentation
l1_ratio = 1 it is an L1 penalty. For 0 < l1_ratio < 1 , the penalty...(i.e. Ridge), as in [.1, .5, .7, .9, .95, .99, 1] . eps float, default=1e-3...scikit-learn.org/stable/modules/generated/sklearn.linear_model.ElasticNetCV.html -
gen_even_slices — scikit-learn 1.7.2 documentation
1, None), slice(1, 2, None), ..., slice(9,...list ( gen_even_slices ( 10 , 1 )) [slice(0, 10, None)] >>> list...scikit-learn.org/stable/modules/generated/sklearn.utils.gen_even_slices.html -
FeatureHasher — scikit-learn 1.7.2 documentation
-1., 0., -1., 0., 1.], [ 0., 0., 0., -1., 0., -1., 0., 0.],...0.], [ 0., -1., 0., 0., 0., 0., 0., 1.]]) fit ( X = None , y...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.FeatureHasher.html -
Release Highlights for scikit-learn 1.6 — sciki...
1 , 6 , np . nan ]) . reshape ( - 1 , 1 ) y = [ 0 ,..., 0 , 1 , 1 ] forest = ExtraTreesClassifier ( random_state =...scikit-learn.org/stable/auto_examples/release_highlights/plot_release_highlights_1_6_0.html -
NMF — scikit-learn 1.7.2 documentation
array ([[ 1 , 1 ], [ 2 , 1 ], [ 3 , 1.2 ], [ 4 , 1 ], [ 5 , 0.8...n\_samples * ||vec(H)||_1\\ &+ 0.5 * alpha\_W * (1 - l1\_ratio) * n\_features...scikit-learn.org/stable/modules/generated/sklearn.decomposition.NMF.html -
KFold — scikit-learn 1.7.2 documentation
3] Test: index=[0 1] Fold 1: Train: index=[0 1] Test: index=[2...X = np . array ([[ 1 , 2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ]])...scikit-learn.org/stable/modules/generated/sklearn.model_selection.KFold.html