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Marvel Reference for 2.x and 1.x | Elastic
x and 1.x: 2.1 Marvel Reference for 2.x and 1.x: 2.0 Marvel...Reference for 2.x and 1.x Marvel Reference for 2.x and 1.x: 2.4 Marvel...www.elastic.co/guide/en/marvel/index.html -
Monotonic Constraints — scikit-learn 1.7.2 docu...
monotonic_cst = { "f_0" : 1 , "f_1" : - 1 } ) . fit ( X_df , y )...) f_1 = rng . rand ( n_samples ) X = np . c_ [ f_0 , f_1 ] noise...scikit-learn.org/stable/auto_examples/ensemble/plot_monotonic_constraints.html -
recall_score — scikit-learn 1.7.2 documentation
[ 1 , 1 , 1 ], [ 0 , 1 , 1 ]] >>> y_pred = [[...[[ 0 , 0 , 0 ], [ 1 , 1 , 1 ], [ 1 , 1 , 0 ]] >>> recall_score...scikit-learn.org/stable/modules/generated/sklearn.metrics.recall_score.html -
Vector Quantization Example — scikit-learn 1.7....
bin_edges [: - 1 ] + ( bin_edges [ 1 :] - bin_edges [: - 1 ]) / 2 bin_center...bin_edges [: - 1 ] + ( bin_edges [ 1 :] - bin_edges [: - 1 ]) / 2 bin_center...scikit-learn.org/stable/auto_examples/cluster/plot_face_compress.html -
Confusion matrix — scikit-learn 1.7.2 documenta...
confusion matrix [[1. 0. 0. ] [0. 0.62 0.38] [0. 0. 1. ]] # Authors:...scikit-learn.org/stable/auto_examples/model_selection/plot_confusion_matrix.html -
pairwise_distances — scikit-learn 1.7.2 documen...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>...deprecated from SciPy 1.9 and will be removed in SciPy 1.11. Note 'matching'...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise_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 -
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 -
empirical_covariance — scikit-learn 1.7.2 docum...
>>> X = [[ 1 , 1 , 1 ],[ 1 , 1 , 1 ],[ 1 , 1 , 1 ], ... [ 0 ,...scikit-learn.org/stable/modules/generated/sklearn.covariance.empirical_covariance.html