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ClassifierTags — scikit-learn 1.7.0 documentation

class sklearn.utils.ClassifierTags(poor_score: bool = False, multi_class: bool = True, multi_label: bool = False)[source]#

Tags for the classifier.

Parameters:

poor_scorebool, default=False

Whether the estimator fails to provide a “reasonable” test-set score, which currently for classification is an accuracy of 0.83 on make_blobs(n_samples=300, random_state=0). The datasets and values are based on current estimators in scikit-learn and might be replaced by something more systematic.

multi_classbool, default=True

Whether the classifier can handle multi-class classification. Note that all classifiers support binary classification. Therefore this flag indicates whether the classifier is a binary-classifier-only or not.

See multi-class in the glossary.

multi_labelbool, default=False

Whether the classifier supports multi-label output: a data point can be predicted to belong to a variable number of classes.

See multi-label in the glossary.

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