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VarianceThreshold — scikit-learn 1.7.2 do...
1 , 4 , 3 ], [ 0 , 1 , 1 , 3 ]] >>>...fit_transform ( X ) array([[2, 0], [1, 4], [1, 1]]) fit ( X , y = None )...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.VarianceThreshold.html -
clone — scikit-learn 1.7.2 documentation
>>> X = [[ - 1 , 0 ], [ 0 , 1 ], [ 0 , - 1 ], [ 1 , 0 ]] >>>...>>> y = [ 0 , 0 , 1 , 1 ] >>> classifier = LogisticRegression...scikit-learn.org/stable/modules/generated/sklearn.base.clone.html -
_safe_indexing — scikit-learn 1.7.2 docum...
axis = 1 ) # select the first column array([1, 3, 5]) On...integer are supported. If axis=1 : to select a single column, indices...scikit-learn.org/stable/modules/generated/sklearn.utils._safe_indexing.html -
binarize — scikit-learn 1.7.2 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 -
Examples — scikit-learn 1.7.2 documentation
scikit-learn 1.1 Release Highlights for scikit-learn 1.1 Release Highlights...scikit-learn 1.7 Release Highlights for scikit-learn 1.7 Release...scikit-learn.org/stable/auto_examples/index.html -
PLSSVD — scikit-learn 1.7.2 documentation
1 , - 0.2 ], ... [ 0.9 , 1.1 ], ... [ 6.2 , 5.9...np . array ([[ 0. , 0. , 1. ], ... [ 1. , 0. , 0. ], ... [ 2. ,...scikit-learn.org/stable/modules/generated/sklearn.cross_decomposition.PLSSVD.html -
trustworthiness — scikit-learn 1.7.2 docu...
1]. It is defined as \[T(k) = 1 - \frac{2}{nk (2n...(2n - 3k - 1)} \sum^n_{i=1} \sum_{j \in \mathcal{N}_{i}^{k}}...scikit-learn.org/stable/modules/generated/sklearn.manifold.trustworthiness.html -
parametrize_with_checks — scikit-learn 1....
scikit-learn 1.6 Release Highlights for scikit-learn 1.6 On this...specific category. Added in version 1.6. expected_failed_checks callable,...scikit-learn.org/stable/modules/generated/sklearn.utils.estimator_checks.parametrize_with_checks.... -
img_to_graph — scikit-learn 1.7.2 documen...
1], [0, 0, 0, 1], [0, 1, 1, 1]]) On this page...np . array ([[ 0 , 0 ], [ 0 , 1 ]]) >>> img_to_graph...scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.image.img_to_graph.html -
ridge_regression — scikit-learn 1.7.2 doc...
0 ] - 1.0 * X [:, 1 ] + 0.1 * rng . standard_normal...>>> coef array([ 1.97, -1., -2.69e-3, -9.27e-4 ]) >>>...scikit-learn.org/stable/modules/generated/sklearn.linear_model.ridge_regression.html