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OPTICS — scikit-learn 1.7.1 documentation
[‘cityblock’, ‘cosine’, ‘euclidean’, ‘l1’, ‘l2’, ‘manhattan’] from...‘chebyshev’, ‘correlation’, ‘dice’, ‘hamming’, ‘jaccard’, ‘kulsinski’,...scikit-learn.org/stable/modules/generated/sklearn.cluster.OPTICS.html -
IncrementalPCA — scikit-learn 1.7.1 documentation
Issue 1-3, pp. 125-141, May 2008. See https://www.cs.toronto.edu...Bishop, 12.2.1 p. 574 or http://www.miketipping.com/papers/met-mppca.pdf...scikit-learn.org/stable/modules/generated/sklearn.decomposition.IncrementalPCA.html -
fetch_20newsgroups — scikit-learn 1.7.1 documen...
array([0, 1, 1, 1, 0, 1, 1, 0, 0, 0]) Gallery examples # Topic extraction...‘~/scikit_learn_data’ subfolders. subset {‘train’, ‘test’, ‘all’}, default=’train’...scikit-learn.org/stable/modules/generated/sklearn.datasets.fetch_20newsgroups.html -
make_low_rank_matrix — scikit-learn 1.7.1 docum...
= 5 , ... tail_strength = 0.01 , ... random_state = 0 , ... )...profile is: ( 1 - tail_strength ) * exp ( - 1.0 * ( i / effective_rank...scikit-learn.org/stable/modules/generated/sklearn.datasets.make_low_rank_matrix.html -
SGDClassifier — scikit-learn 1.7.1 documentation
{‘hinge’, ‘log_loss’, ‘modified_huber’, ‘squared_hinge’, ‘perceptron’,...‘perceptron’, ‘squared_error’, ‘huber’, ‘epsilon_insensitive’, ‘squar...scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDClassifier.html -
mean_pinball_loss — scikit-learn 1.7.1 document...
mean_pinball_loss ( y_true , [ 1 , 2 , 4 ], alpha = 0.9 ) 0.03... >>> mean_pinball_loss...1 , 2 , 4 ], alpha = 0.1 ) 0.3... >>> mean_pinball_loss ( y_true...scikit-learn.org/stable/modules/generated/sklearn.metrics.mean_pinball_loss.html -
ValidationCurveDisplay — scikit-learn 1.7.1 doc...
test_scores , score_name = "Score" ... ) >>> display . plot () <...> >>>...instance (e.g., GroupKFold ). cv int, cross-validation generator...scikit-learn.org/stable/modules/generated/sklearn.model_selection.ValidationCurveDisplay.html -
OrthogonalMatchingPursuit — scikit-learn 1.7.1 ...
12. (December 1993), pp. 3397-3415. ( https://www.di.ens.fr/~m...OrthogonalMatchingPu () . fit ( X , y ) >>> reg . score ( X , y ) 0.9991 >>>...scikit-learn.org/stable/modules/generated/sklearn.linear_model.OrthogonalMatchingPursuit.html -
NearestCentroid — scikit-learn 1.7.1 documentation
np . array ([[ - 1 , - 1 ], [ - 2 , - 1 ], [ - 3 , - 2 ], [ 1...1 , 1 ], [ 2 , 1 ], [ 3 , 2 ]]) >>> y = np . array ([ 1 , 1 ,...scikit-learn.org/stable/modules/generated/sklearn.neighbors.NearestCentroid.html -
lars_path — scikit-learn 1.7.1 documentation
random_state = 0 ... ) >>> true_coef array([ 0. , 0. , 0. , 97.9, 45.7])...method=’lasso’ is: ( 1 / ( 2 * n_samples )) * || y - Xw ||^ 2_2 + alpha *...scikit-learn.org/stable/modules/generated/sklearn.linear_model.lars_path.html