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paired_cosine_distances — scikit-learn 1.8.0 do...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.paired_cosine_distances.html -
LeavePOut — scikit-learn 1.8.0 documentation
3] Test: index=[0 1] Fold 1: Train: index=[1 3] Test: index=[0...index=[1 2] Fold 4: Train: index=[0 2] Test: index=[1 3] Fold...scikit-learn.org/stable/modules/generated/sklearn.model_selection.LeavePOut.html -
DotProduct — scikit-learn 1.8.0 documentation
1)\) priors on the coefficients of \(x_d (d = 1, . . ....nels. DotProduct ( sigma_0 = 1.0 , sigma_0_bounds = (1e-05, 100000.0)...scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.kernels.DotProduct.html -
RepeatedKFold — scikit-learn 1.8.0 documentation
array ([[ 1 , 2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ]])...>>> y = np . array ([ 0 , 0 , 1 , 1 ]) >>> rkf = RepeatedKFold (...scikit-learn.org/stable/modules/generated/sklearn.model_selection.RepeatedKFold.html -
binarize — scikit-learn 1.8.0 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 -
chi2 — scikit-learn 1.8.0 documentation
array ([[ 1 , 1 , 3 ], ... [ 0 , 1 , 5 ], ... [ 5 , 4 , 1 ], ......y = np . array ([ 1 , 1 , 0 , 0 , 2 , 2 ]) >>> chi2_stats , p_values...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.chi2.html -
silhouette_score — scikit-learn 1.8.0 documenta...
The best value is 1 and the worst value is -1. Values near 0 indicate...2 <= n_labels <= n_samples - 1 . This function returns the mean...scikit-learn.org/stable/modules/generated/sklearn.metrics.silhouette_score.html -
KMeans — scikit-learn 1.8.0 documentation
scikit-learn 1.1 Release Highlights for scikit-learn 1.1 Clustering...X = np . array ([[ 1 , 2 ], [ 1 , 4 ], [ 1 , 0 ], ... [ 10 , 2...scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html -
MaxAbsScaler — scikit-learn 1.8.0 documentation
-1. , 1. ], [ 1. , 0. , 0. ], [ 0. , 1. , -0.5]]) fit...= [[ 1. , - 1. , 2. ], ... [ 2. , 0. , 0. ], ... [ 0. , 1. , -...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.MaxAbsScaler.html -
cosine_similarity — scikit-learn 1.8.0 document...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.cosine_similarity.html