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.
- 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.
- 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 arandom_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.