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MultinomialNB — scikit-learn 1.7.2 documentation
2. Changed in version 1.4: The default...)) >>> y = np . array ([ 1 , 2 , 3 , 4 , 5 , 6 ]) >>> from sklearn.naive_bayes...scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.MultinomialNB.html -
lars_path — scikit-learn 1.7.2 documentation
is: ( 1 / ( 2 * n_samples )) * || y - Xw ||^ 2_2 + alpha * ||...copy_X = True , eps = np.float64(2.220446049250313e-16) , copy_Gram...scikit-learn.org/stable/modules/generated/sklearn.linear_model.lars_path.html -
log_loss — scikit-learn 1.7.2 documentation
2 ], [ .35 , .65 ]]) 0.21616 Gallery...scikit-learn.org/stable/modules/generated/sklearn.metrics.log_loss.html -
LearningCurveDisplay — scikit-learn 1.7.2 docum...
2 Release Highlights for scikit-learn 1.2 On this page...visualization. Added in version 1.2. Parameters : train_sizes ndarray...scikit-learn.org/stable/modules/generated/sklearn.model_selection.LearningCurveDisplay.html -
LogisticRegressionCV — scikit-learn 1.7.2 docum...
[: 2 , :]) array([0, 0]) >>> clf . predict_proba ( X [: 2 , :])...SAGA solver. Added in version 1.2: newton-cholesky solver. Multinomial...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegressionCV.html -
TargetEncoder — scikit-learn 1.7.2 documentation
for 2 features (f) and 3 classes (c),...] * 5 + [ 20.1 ] * 25 + [ 21.2 ] * 8 + [ 49 ] * 30 >>> enc_auto...scikit-learn.org/stable/modules/generated/sklearn.preprocessing.TargetEncoder.html -
cluster_optics_dbscan — scikit-learn 1.7.2 docu...
2 ], [ 2 , 5 ], [ 3 , 6 ], ... [ 8... ( ... X , ... min_samples = 2 , ... max_eps = np . inf , ......scikit-learn.org/stable/modules/generated/sklearn.cluster.cluster_optics_dbscan.html -
StratifiedGroupKFold — scikit-learn 1.7.2 docum...
index=[ 0 1 2 3 15 16] group=[1 1 2 2 8 8] Fold 2: Train: index=[...index=[ 0 1 2 3 7 8 9 10 11 15 16] group=[1 1 2 2 4 5 5 5 5 8...scikit-learn.org/stable/modules/generated/sklearn.model_selection.StratifiedGroupKFold.html -
LogisticRegression — scikit-learn 1.7.2 documen...
[: 2 , :]) array([0, 0]) >>> clf . predict_proba ( X [: 2 , :])...‘lbfgs’ in 0.22. Added in version 1.2: newton-cholesky solver. Multinomial...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html -
shuffle — scikit-learn 1.7.2 documentation
2)> >>> X_sparse . toarray () array([[0., 0.], [2., 1.],...y array([2, 1, 0]) >>> shuffle ( y , n_samples = 2 , random_state...scikit-learn.org/stable/modules/generated/sklearn.utils.shuffle.html