class_docstr: Wrapper class for scikit-learn regression models.
docstr: Create a copy of the classifier that can be refit from scratch.
  
  :return: new estimator
docstr_tok: ["Create","a","copy","of","the","classifier","that","can","be","refit","from","scratch",".",":","return",":","new","estimator"]
code: def clone_for_refitting(self) -> "ScikitlearnRegressor":
      """
      Create a copy of the classifier that can be refit from scratch.
  
      :return: new estimator
      """
      import sklearn
  
      clone = type(self)(sklearn.base.clone(self.model))
      params = self.get_params()
      del params["model"]
      clone.set_params(**params)
      return clone
  
imports: import logging
  import os
  import pickle
  from copy import deepcopy
  from typing import List, Optional, Tuple, Union, TYPE_CHECKING
  import numpy
  from art.estimators.scikitlearn import ScikitlearnEstimator
  from art.estimators.regression.regressor import RegressorMixin
  from art import config
label_desc: Use image node_id 6 for calling the ScikitlearnRegressor obj's underlying member method code with example usage: obj.clone_for_refitting() and returns: clone