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confusion_matrix — scikit-learn 1.7.2 documenta...
= [ 2 , 0 , 2 , 2 , 0 , 1 ] >>> y_pred = [ 0 , 0 , 2 , 2 , 0...0 , 2 ] >>> confusion_matrix ( y_true , y_pred ) array([[2, 0,...scikit-learn.org/stable/modules/generated/sklearn.metrics.confusion_matrix.html -
KFold — scikit-learn 1.7.2 documentation
2 ], [ 3 , 4 ], [ 1 , 2 ], [ 3 , 4 ]]) >>>...array ([ 1 , 2 , 3 , 4 ]) >>> kf = KFold ( n_splits = 2 ) >>> kf...scikit-learn.org/stable/modules/generated/sklearn.model_selection.KFold.html -
LassoLarsIC — scikit-learn 1.7.2 documentation
[[ - 2 , 2 ], [ - 1 , 1 ], [ 0 , 0 ], [ 1 , 1 ], [ 2 , 2 ]] >>>...is: ( 1 / ( 2 * n_samples )) * || y - Xw ||^ 2_2 + alpha * ||...scikit-learn.org/stable/modules/generated/sklearn.linear_model.LassoLarsIC.html -
hamming_loss — scikit-learn 1.7.2 documentation
2 , 3 , 4 ] >>> y_true = [ 2 , 2 , 3 , 4 ] >>>...[ 1 , 1 ]]), np . zeros (( 2 , 2 ))) 0.75 Gallery examples #...scikit-learn.org/stable/modules/generated/sklearn.metrics.hamming_loss.html -
kmeans_plusplus — scikit-learn 1.7.2 documentation
2 ], [ 1 , 4 ], [ 1 , 0 ], ... [ 10 , 2 ], [ 10 , 4...n_clusters = 2 , random_state = 0 ) >>> centers array([[10, 2], [ 1,...scikit-learn.org/stable/modules/generated/sklearn.cluster.kmeans_plusplus.html -
HalvingGridSearchCV — scikit-learn 1.7.2 docume...
to a small value: n_splits * 2 when resource='n_samples' for...problem n_classes * n_splits * 2 when resource='n_samples' for...scikit-learn.org/stable/modules/generated/sklearn.model_selection.HalvingGridSearchCV.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 -
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 -
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 -
accuracy_score — scikit-learn 1.7.2 documentation
2 , 1 , 3 ] >>> y_true = [ 0 , 1 , 2 , 3 ] >>> accuracy_score...], [ 1 , 1 ]]), np . ones (( 2 , 2 ))) 0.5 Gallery examples # Plot...scikit-learn.org/stable/modules/generated/sklearn.metrics.accuracy_score.html