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TimeSeriesSplit — scikit-learn 1.8.0 docu...
2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 ,...1] Test: index=[2] Fold 2: Train: index=[0 1 2] Test: index=[3]...scikit-learn.org/stable/modules/generated/sklearn.model_selection.TimeSeriesSplit.html -
check_symmetric — scikit-learn 1.8.0 docu...
2 ], [ 1 , 0 , 1 ], [ 2 , 1 , 0 ]]) >>>...symmetric_array ) array([[0, 1, 2], [1, 0, 1], [2, 1, 0]]) >>>...scikit-learn.org/stable/modules/generated/sklearn.utils.validation.check_symmetric.html -
SpectralClustering — scikit-learn 1.8.0 d...
( - dist_matrix ** 2 / ( 2. * delta ** 2 )) where delta is a...normalized graph cuts [1] , [2] . When calling fit , an affinity...scikit-learn.org/stable/modules/generated/sklearn.cluster.SpectralClustering.html -
enet_path — scikit-learn 1.8.0 documentation
is: ( 1 / ( 2 * n_samples )) * || Y - XW || _Fro ^ 2 + alpha *...mono-output tasks it is: 1 / ( 2 * n_samples ) * || y - Xw ||^...scikit-learn.org/stable/modules/generated/sklearn.linear_model.enet_path.html -
multilabel_confusion_matrix — scikit-lear...
2]], [[5, 0], [1, 0]], [[2, 1], [1, 2]]]) On this...ndarray of shape (n_outputs, 2, 2) A 2x2 confusion matrix corresponding...scikit-learn.org/stable/modules/generated/sklearn.metrics.multilabel_confusion_matrix.html -
Selecting the number of clusters with silhouett...
and 2 columns fig , ( ax1 , ax2 ) = plt . subplots ( 1 , 2 ) fig...ambivalent in deciding between 2 and 4. Also from the thickness...scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_silhouette_analysis.html -
ShuffleSplit — scikit-learn 1.8.0 documen...
2 , 1 , 2 , 1 , 2 ]) >>> rs = ShuffleSplit...Test: index=[5 2] Fold 1: Train: index=[4 0 2 5] Test: index=[1...scikit-learn.org/stable/modules/generated/sklearn.model_selection.ShuffleSplit.html -
Better Binary Quantization (BBQ) in Lucene and ...
< 0 ) + ( 2 < < 1 ) + ( 1 < < 2 ) + ( 2 < <...<< 0) + (2 << 1) + (1 << 2) + (2 << 3) =...www.elastic.co/search-labs/blog/better-binary-quantization-lucene-elasticsearch -
mean_absolute_error — scikit-learn 1.8.0 ...
2 , 7 ] >>> y_pred = [ 2.5 , 0.0 , 2 , 8 ] >>>...>>> y_pred = [[ 0 , 2 ], [ - 1 , 2 ], [ 8 , - 5 ]] >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_absolute_error.html -
mean_squared_error — scikit-learn 1.8.0 d...
2 , 7 ] >>> y_pred = [ 2.5 , 0.0 , 2 , 8 ] >>>...>>> y_pred = [[ 0 , 2 ],[ - 1 , 2 ],[ 8 , - 5 ]] >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_squared_error.html