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add_dummy_feature — scikit-learn 1.7.1 document...
1 ], [ 1 , 0 ]]) array([[1., 0., 1.], [1., 1., 0.]])...add_dummy_feature ( X , value = 1.0 ) [source] # Augment dataset...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.add_dummy_feature.html -
pair_confusion_matrix — scikit-learn 1.7.1 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 -
Lasso, Lasso-LARS, and Elastic Net paths — scik...
legend (( l1 [ - 1 ], l2 [ - 1 ]), ( "Lasso" , "LARS" ),...plt . legend (( l1 [ - 1 ], l2 [ - 1 ]), ( "Lasso" , "Elastic-Net"...scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_lasso_lars_elasticnet_path.html -
check_X_y — scikit-learn 1.7.1 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/stable/modules/generated/sklearn.utils.check_X_y.html -
explained_variance_score — scikit-learn 1.7.1 d...
1 ], [ - 1 , 1 ], [ 7 , - 6 ]] >>> y_pred...cross-validation). Added in version 1.1. Returns : score float or ndarray...scikit-learn.org/stable/modules/generated/sklearn.metrics.explained_variance_score.html -
inplace_csr_row_normalize_l2 — scikit-learn 1.7...
1 , 2 , 3 ]) >>> data = np . array ([ 1.0 , 2.0 , 3.0...0. ], [0. , 0. , 1. , 0. ], [0. , 0. , 0. , 1. ]]) On this page...scikit-learn.org/stable/modules/generated/sklearn.utils.sparsefuncs_fast.inplace_csr_row_normaliz... -
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 1.7.1 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 1.7.1 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 -
paired_cosine_distances — scikit-learn 1.7.1 do...
[ 1 , 1 , 1 ]] >>> Y = [[ 1 , 0 , 0 ], [ 1 , 1 , 0 ]] >>>...scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.paired_cosine_distances.html