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Tags — scikit-learn 1.8.dev0 documentation

class sklearn.utils.Tags(estimator_type: str | None, target_tags: ~sklearn.utils._tags.TargetTags, transformer_tags: ~sklearn.utils._tags.TransformerTags | None = None, classifier_tags: ~sklearn.utils._tags.ClassifierTags | None = None, regressor_tags: ~sklearn.utils._tags.RegressorTags | None = None, array_api_support: bool = False, no_validation: bool = False, non_deterministic: bool = False, requires_fit: bool = True, _skip_test: bool = False, input_tags: ~sklearn.utils._tags.InputTags = <factory>)[source]#

Tags for the estimator.

See Estimator Tags for more information.

Parameters:

estimator_typestr or None

The type of the estimator. Can be one of: - “classifier” - “regressor” - “transformer” - “clusterer” - “outlier_detector” - “density_estimator”

target_tagsTargetTags

The target(y) tags.

transformer_tagsTransformerTags or None

The transformer tags.

classifier_tagsClassifierTags or None

The classifier tags.

regressor_tagsRegressorTags or None

The regressor tags.

array_api_supportbool, default=False

Whether the estimator supports Array API compatible inputs.

no_validationbool, default=False

Whether the estimator skips input-validation. This is only meant for stateless and dummy transformers!

non_deterministicbool, default=False

Whether the estimator is not deterministic given a fixed random_state.

requires_fitbool, default=True

Whether the estimator requires to be fitted before calling one of transform, predict, predict_proba, or decision_function.

_skip_testbool, default=False

Whether to skip common tests entirely. Don’t use this unless you have a very good reason.

input_tagsInputTags

The input data(X) tags.

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