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LeavePGroupsOut — scikit-learn 1.5.2 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 -
make_pipeline — scikit-learn 1.5.2 documentation
2 Release Highlights for scikit-learn 1.2 Release Highlights...scikit-learn.org/stable/modules/generated/sklearn.pipeline.make_pipeline.html -
MultiTaskLassoCV — scikit-learn 1.5.2 documenta...
is: ( 1 / ( 2 * n_samples )) * || y - Xw ||^ 2_2 + alpha * ||...is: ( 1 / ( 2 * n_samples )) * || Y - XW ||^ Fro_2 + alpha * ||...scikit-learn.org/stable/modules/generated/sklearn.linear_model.MultiTaskLassoCV.html -
resample — scikit-learn 1.5.2 documentation
2)> >>> X_sparse . toarray () array([[1., 0.], [2., 1.],...= np . array ([[ 1. , 0. ], [ 2. , 1. ], [ 0. , 0. ]]) >>> y =...scikit-learn.org/stable/modules/generated/sklearn.utils.resample.html -
JSONによる検索結果の出力
2 11.1 11.0 10.3 10.2 10.1 10.0 9.4 9.3 9.2 9.1 9.0 8.0...13.4 13.3 13.2 13.1 13.0 12.7 12.6 12.5 12.4 12.3 12.2 12.1 12.0...fess.codelibs.org/ja/4.0/user/json-response.html -
AdditiveChi2Sampler — scikit-learn 1.5.2 docume...
sample_steps = 2 , sample_interval = None ) [source]...original space is transformed into 2*sample_steps-1 features, where...scikit-learn.org/stable/modules/generated/sklearn.kernel_approximation.AdditiveChi2Sampler.html -
PredefinedSplit — scikit-learn 1.5.2 documentation
2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ]]) >>>...index=[1 2 3] Test: index=[0] Fold 1: Train: index=[0 2] Test:...scikit-learn.org/stable/modules/generated/sklearn.model_selection.PredefinedSplit.html -
indexable — scikit-learn 1.5.2 documentation
2 , 3 ], np . array ([ 2 , 3 , 4 ]), None ,...indexable ( * iterables ) [[1, 2, 3], array([2, 3, 4]), None, <...Sparse...dtype...scikit-learn.org/stable/modules/generated/sklearn.utils.indexable.html -
LarsCV — scikit-learn 1.5.2 documentation
float \(R^2\) of self.predict(X) w.r.t. y . Notes The \(R^2\) score...n_jobs = None , eps = np.float64(2.220446049250313e-16) , copy_X...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LarsCV.html -
Product — scikit-learn 1.5.2 documentation
takes two kernels \(k_1\) and \(k_2\) and combines them via \[k_{prod}(X,...\[k_{prod}(X, Y) = k_1(X, Y) * k_2(X, Y)\] Note that the __mul__ magic...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.Product.html