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Sample pipeline for text feature extraction and...
2)`` means unigrams and bigrams, and ``(2, 2)`` means...unigrams, ``(1, 2)`` means unigrams and bigrams, and ``(2, 2)`` means...scikit-learn.org/stable/auto_examples/model_selection/plot_grid_search_text_feature_extraction.html -
SelectorMixin — scikit-learn 1.8.0 docume...
mask [: 2 ] = True # select the first two...fit_transform ( X , y ) . shape (150, 2) fit_transform ( X , y = None...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.SelectorMixin.html -
maxabs_scale — scikit-learn 1.8.0 documen...
maxabs_scale >>> X = [[ - 2 , 1 , 2 ], [ - 1 , 0 , 1 ]] >>>...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.maxabs_scale.html -
GaussianMixture — scikit-learn 1.8.0 docu...
2 ], [ 1 , 4 ], [ 1 , 0 ], [ 10 , 2 ], [ 10 , 4 ],...gm . means_ array([[10., 2.], [ 1., 2.]]) >>> gm . predict...scikit-learn.org/stable/modules/generated/sklearn.mixture.GaussianMixture.html -
homogeneity_score — scikit-learn 1.8.0 do...
2 ])) 1.000000 >>> print...([ 0 , 0 , 1 , 1 ], [ 0 , 1 , 2 , 3 ])) 1.000000 Clusters that...scikit-learn.org/stable/modules/generated/sklearn.metrics.homogeneity_score.html -
BernoulliRBM — scikit-learn 1.8.0 documen...
Contrastive Divergence (PCD) [2]. The time complexity of this...this implementation is O(d ** 2) assuming d ~ n_features ~ n_components....scikit-learn.org/stable/modules/generated/sklearn.neural_network.BernoulliRBM.html -
plot_discretization_strategies.rst.txt
[2, 4], [8, 8]]) centers_1 = np.array([[0,...form(-3, 3, size=(n_samples, 2)), make_blobs( n_samples=[ n_samples...scikit-learn.org/stable/_sources/auto_examples/preprocessing/plot_discretization_strategies.rst.txt -
Programador de Tareas
configuración de rastreo web son 1 y 2, y el ID de configuración de rastreo...webConfigIds ([ "1" , "2" ] as String []) . fileConfigIds...fess.codelibs.org/es/15.3/admin/scheduler-guide.html -
GaussianNB — scikit-learn 1.8.0 documenta...
[ - 2 , - 1 ], [ - 3 , - 2 ], [ 1 , 1 ], [ 2 , 1 ], [ 3...3 , 2 ]]) >>> Y = np . array ([ 1 , 1 , 1 , 2 , 2 , 2...scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.GaussianNB.html -
average_precision_score — scikit-learn 1....
2 , 2 ]) >>> y_scores = np...], ... [ 0.2 , 0.3 , 0.5 ], ... [ 0.4 , 0.4 , 0.2 ], ... [ 0.1...scikit-learn.org/stable/modules/generated/sklearn.metrics.average_precision_score.html