sklearn.base.clone

sklearn.base.clone(estimator, *, safe=True)[source]

Construct a new unfitted estimator with the same parameters.

Clone does a deep copy of the model in an estimator without actually copying attached data. It returns a new estimator with the same parameters that has not been fitted on any data.

Changed in version 1.3: Delegates to estimator.__sklearn_clone__ if the method exists.

Parameters:
estimator{list, tuple, set} of estimator instance or a single estimator instance

The estimator or group of estimators to be cloned.

safebool, default=True

If safe is False, clone will fall back to a deep copy on objects that are not estimators. Ignored if estimator.__sklearn_clone__ exists.

Returns:
estimatorobject

The deep copy of the input, an estimator if input is an estimator.

Notes

If the estimator’s random_state parameter is an integer (or if the estimator doesn’t have a random_state parameter), an exact clone is returned: the clone and the original estimator will give the exact same results. Otherwise, statistical clone is returned: the clone might return different results from the original estimator. More details can be found in Controlling randomness.