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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 -
add_dummy_feature — scikit-learn 1.7.2 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 -
label_ranking_loss — scikit-learn 1.7.2 documen...
1 ], [ 1 , 0.2 , 0.1 ]] >>> label_ranking_loss...label_ranking_loss >>> y_true = [[ 1 , 0 , 0 ], [ 0 , 0 , 1 ]] >>> y_score = [[...scikit-learn.org/stable/modules/generated/sklearn.metrics.label_ranking_loss.html -
Gradient Boosting Out-of-Bag estimates — scikit...
subsample < 1.0 ), the estimates are derived...y = random_state . binomial ( 1 , p , size = n_samples ) X = np...scikit-learn.org/stable/auto_examples/ensemble/plot_gradient_boosting_oob.html -
pair_confusion_matrix — scikit-learn 1.7.2 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 -
Gaussian Mixture Model Sine Curve — scikit-lear...
1 , 1 + index ) for i , ( mean , covar...random . normal ( 0 , 0.1 ) X [ i , 1 ] = 3.0 * ( np . sin ( x...scikit-learn.org/stable/auto_examples/mixture/plot_gmm_sin.html -
Gaussian Process for Machine Learning — scikit-...
Examples concerning the sklearn.gaussian_process module. Ability of Gaussian process regression (GPR) to estimate data noise-level Comparison of kernel ridge and Gaussian process regression Forecas...scikit-learn.org/stable/auto_examples/gaussian_process/index.html -
check_X_y — scikit-learn 1.7.2 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 1.7.2 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 -
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