code: def __init__(
      self,
      capping_method: str = "gaussian",
      tail: str = "right",
      fold: Union[int, float] = 3,
      variables: Union[None, int, str, List[Union[str, int]]] = None,
      missing_values: str = "raise",
  ) -> None:
      if capping_method not in ["gaussian", "iqr", "quantiles", "mad"]:
          raise ValueError(
              "capping_method takes only values 'gaussian', 'iqr', 'mad', 'quantiles'"
          )
  
      if tail not in ["right", "left", "both"]:
          raise ValueError(
              "tail takes only values 'right', 'left' or 'both'"
          )
  
      if fold <= 0:
          raise ValueError("fold takes only positive numbers")
  
      if capping_method == "quantiles" and fold > 0.2 and fold != 3:
          raise ValueError(
              "with capping_method ='quantiles', fold takes values between 0 and "
              "0.20 only."
          )
  
      if missing_values not in ["raise", "ignore"]:
          raise ValueError(
              "missing_values takes only values 'raise' or 'ignore'"
          )
  
      self.capping_method = capping_method
      self.tail = tail
      self.fold = (
          0.05
          if (capping_method == "quantiles") & (fold == 3)
          else fold
      )
      self.variables = _check_init_parameter_variables(variables)
      self.missing_values = missing_values
  
imports: from typing import List, Optional, Union
  import pandas
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.utils.validation import check_is_fitted
  from feature_engine._variable_handling.init_parameter_checks import _check_init_parameter_variables
  from feature_engine._variable_handling.variable_type_selection import _find_or_check_numerical_variables
  from feature_engine.dataframe_checks import _check_contains_inf, _check_contains_na, _check_X_matches_training_df, check_X
  from feature_engine._base_transformers.mixins import GetFeatureNamesOutMixin
  from feature_engine.tags import _return_tags
label_desc: Use image node_id 1 to create a new WinsorizerBase object from inherited base classes: BaseOutlier with example: obj = WinsorizerBase(capping_method, tail, fold, variables, missing_values)