code: def __init__(
      self,
      regressor=None,
      *,
      power_transformer_method="box-cox",
      power_transformer_standardize=True,
      **kwargs,
  ):
      self.regressor = regressor
      self.power_transformer_method = power_transformer_method
      self.power_transformer_standardize = power_transformer_standardize
      self.transformer = PowerTransformer(
          method=self.power_transformer_method,
          standardize=self.power_transformer_standardize,
      )
      self.func = None
      self.inverse_func = None
      self.check_inverse = False
      self._fit_vars = set()
      self.set_params(**kwargs)
  
imports: import sklearn.compose
  from sklearn.base import BaseEstimator, ClassifierMixin, clone
  from sklearn.compose import TransformedTargetRegressor
  from sklearn.preprocessing import PowerTransformer
  from sklearn.utils.validation import check_is_fitted
label_desc: Use image node_id 1 to create a new PowerTransformedTargetRegressor object from inherited base classes: sklearn.compose with example: obj = PowerTransformedTargetRegressor(regressor)