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Robust covariance estimation and Mahalanobis di...
where feature 1 has a standard deviation equal to 1 and feature...np . arange ( 1 , n_features ), np . arange ( 1 , n_features )]...scikit-learn.org/stable/auto_examples/covariance/plot_mahalanobis_distances.html -
make_friedman2 — scikit-learn 1.7.2 documentation
1 ] <= 560 * pi , 0 <= X [:, 2 ] <= 1 , 1 <= X [:, 3...** 2 + ( X [:, 1 ] * X [:, 2 ] - 1 / ( X [:, 1 ] * X [:, 3 ]))...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_friedman2.html -
Common pitfalls in the interpretation of coeffi...
1.e-03, 1.e-02, 1.e-01, 1.e+00, 1.e+01, 1.e+02, 1.e+03, 1.e+04,...1.e-04, 1.e-03, 1.e-02, 1.e-01, 1.e+00, 1.e+01, 1.e+02, 1.e+03, 1.e+04,...scikit-learn.org/stable/auto_examples/inspection/plot_linear_model_coefficient_interpretation.html -
contingency_matrix — scikit-learn 1.7.2 documen...
labels_pred ) array([[1, 1, 0], [0, 1, 1], [1, 0, 1]]) On this page..., 0 , 1 , 1 , 2 , 2 ] >>> labels_pred = [ 1 , 0 , 2 , 1 , 0 ,...scikit-learn.org/stable/modules/generated/sklearn.metrics.cluster.contingency_matrix.html -
cosine_distances — scikit-learn 1.7.2 documenta...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>...cosine_distances ( X , Y ) array([[1. , 1. ], [0.422, 0.183]]) On this...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.cosine_distances.html -
Compare the effect of different scalers on data...
cutoffs_X1 [ 1 ]], axis = 1 ) plot_distribution ( axarr [ 1 ], X [ non_outliers_mask...left , width = 0.1 , 0.22 bottom , height = 0.1 , 0.7 bottom_h...scikit-learn.org/stable/auto_examples/preprocessing/plot_all_scaling.html -
laplacian_kernel — scikit-learn 1.7.2 documenta...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>...K(x, y) = exp(-gamma ||x-y||_1) for each pair of rows x in X...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.laplacian_kernel.html -
Label Propagation digits: Demonstrating perform...
support 0 1.00 1.00 1.00 27 1 0.82 1.00 0.90 37 2 1.00 0.86 0.92...0.92 28 3 1.00 0.80 0.89 35 4 0.92 1.00 0.96 24 5 0.74 0.94 0.83...scikit-learn.org/stable/auto_examples/semi_supervised/plot_label_propagation_digits.html -
rbf_kernel — scikit-learn 1.7.2 documentation
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>...default=None If None, defaults to 1.0 / n_features. Returns : kernel...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.rbf_kernel.html -
check_estimator — scikit-learn 1.7.2 documentation
since version 1.6: generate_only will be removed in 1.8. Use est...since version 1.6: generate_only will be removed in 1.8. Use est...scikit-learn.org/stable/modules/generated/sklearn.utils.estimator_checks.check_estimator.html