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paired_euclidean_distances — scikit-learn 1.7.d...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>...paired_euclidean_distances ( X , Y ) array([1., 1.]) On this page Show Source...scikit-learn.org/dev/modules/generated/sklearn.metrics.pairwise.paired_euclidean_distances.html -
pair_confusion_matrix — scikit-learn 1.6.0 docu...
1 , 1 ], [ 1 , 1 , 0 , 0 ]) array([[8,...pair_confusion_matrix ([ 0 , 0 , 1 , 2 ], [ 0 , 0 , 1 , 1 ]) array([[8, 2],...scikit-learn.org/stable/modules/generated/sklearn.metrics.cluster.pair_confusion_matrix.html -
FastICA on 2D point clouds — scikit-learn 1.6.0...
array ([[ 1 , 1 ], [ 0 , 2 ]]) # Mixing matrix...( 42 ) S = rng . standard_t ( 1.5 , size = ( 20000 , 2 )) S [:,...scikit-learn.org/stable/auto_examples/decomposition/plot_ica_vs_pca.html -
Plotting Cross-Validated Predictions — scikit-l...
ax = axs [ 1 ], random_state = 0 , ) axs [ 1 ] . set_title...scikit-learn.org/stable/auto_examples/model_selection/plot_cv_predict.html -
check_X_y — scikit-learn 1.7.dev0 documentation
ensure_min_samples = 1 , ensure_min_features = 1 , y_numeric = False...>>> X = [[ 1 , 2 ], [ 3 , 4 ], [ 5 , 6 ]] >>> y = [ 1 , 2 , 3 ]...scikit-learn.org/dev/modules/generated/sklearn.utils.check_X_y.html -
Ordinary Least Squares Example — scikit-learn 1...
legend () ax [ 1 ] . scatter ( X_test , y_test...label = "Test data points" ) ax [ 1 ] . plot ( X_test , y_pred , linewidth...scikit-learn.org/stable/auto_examples/linear_model/plot_ols.html -
OOB Errors for Random Forests — scikit-learn 1....
validated whilst being trained [ 1 ] . The example below demonstrates...= 25 , n_clusters_per_class = 1 , n_informative = 15 , random_state...scikit-learn.org/stable/auto_examples/ensemble/plot_ensemble_oob.html -
Blind source separation using FastICA — scikit-...
array ([[ 1 , 1 , 1 ], [ 0.5 , 2 , 1.0 ], [ 1.5 , 1.0 , 2.0 ]])...models , names ), 1 ): plt . subplot ( 4 , 1 , ii ) plt . title...scikit-learn.org/stable/auto_examples/decomposition/plot_ica_blind_source_separation.html -
mutual_info_score — scikit-learn 1.6.0 document...
1 , 1 , 0 , 1 , 0 ] >>> labels_pred = [ 0 , 1 , 0 , 0...as: \[MI(U,V)=\sum_{i=1}^{|U|} \sum_{j=1}^{|V|} \frac{|U_i\cap...scikit-learn.org/stable/modules/generated/sklearn.metrics.mutual_info_score.html -
nan_euclidean_distances — scikit-learn 1.6.0 do...
6] and [1, na, 4, 5] is: \[\sqrt{\frac{4}{2}((3-1)^2 + (6-5)^2)}\]...float ( "NaN" ) >>> X = [[ 0 , 1 ], [ 1 , nan ]] >>> nan_euclidean_distances...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.nan_euclidean_distances.html