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Concatenating multiple feature extraction metho...
features__univ_select__k=1, svm__C=0.1 [CV 1/5; 1/18] END features_...nts=1, features__univ_select__k=1, svm__C=0.1;, score=1.000 total...scikit-learn.org/stable/auto_examples/compose/plot_feature_union.html -
Version 0.17 — scikit-learn 1.7.0 documentation
1 # February 18, 2016 Changelog...meta-estimator with n_jobs > 1 used with a large grid of parameters...scikit-learn.org/stable/whats_new/v0.17.html -
precision_recall_curve — scikit-learn 1.7.0 doc...
y_true is in {-1, 1} or {0, 1}, pos_label is set to 1, otherwise...0.66666667, 0.5 , 1. , 1. ]) >>> recall array([1. , 1. , 0.5, 0.5,...scikit-learn.org/stable/modules/generated/sklearn.metrics.precision_recall_curve.html -
Demonstration of k-means assumptions — scikit-l...
axs [ 1 , 0 ] . set_title ( "Unequal Variance" ) axs [ 1 , 1 ] ....X_filtered [:, 1 ], c = y_filtered ) axs [ 1 , 1 ] . set_title...scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_assumptions.html -
XML results output
1 11.0 10.3 10.2 10.1 10.0 9.4 9.3 9.2 9.1 9.0 8.0 7.0...13.3 13.2 13.1 13.0 12.7 12.6 12.5 12.4 12.3 12.2 12.1 12.0 11.4...fess.codelibs.org/4.0/user/xml-response.html -
non_negative_factorization — scikit-learn 1.7.0...
array ([[ 1 , 1 ], [ 2 , 1 ], [ 3 , 1.2 ], [ 4 , 1 ], [ 5 , 0.8...n\_samples * ||vec(H)||_1\\ &+ 0.5 * alpha\_W * (1 - l1\_ratio) * n\_features...scikit-learn.org/stable/modules/generated/sklearn.decomposition.non_negative_factorization.html -
add_dummy_feature — scikit-learn 1.7.0 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 -
Recognizing hand-written digits — scikit-learn ...
0 0 0 1 0 0 0 0 0] [ 0 88 1 0 0 0 0 0 1 1] [ 0 0 85 1 0 0 0 0...0 0 88 1 0 0 2] [ 0 1 0 0 0 0 90 0 0 0] [ 0 0 0 0 0 1 0 88 0...scikit-learn.org/stable/auto_examples/classification/plot_digits_classification.html -
pair_confusion_matrix — scikit-learn 1.7.0 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 -
check_X_y — scikit-learn 1.7.0 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