class_docstr: Fill the missing values in continuous columns.
class_docstr_tok: ["Fill","the","missing","values","in","continuous","columns","."]
code: def __init__(
      self,
      cat_names,
      cont_names,
      fill_strategy=FILL_MEDIAN,
      add_col=True,
      fill_val=0.0,
  ):
      super().__init__(cat_names, cont_names)
      self.fill_strategy = fill_strategy
      self.add_col = add_col
      self.fill_val = fill_val
      self.na_dict = None
  
imports: from ..None import utils
  from ..imports import *
  from ..preprocessor import Preprocessor
  from numbers import Number
  from types import SimpleNamespace
  from typing import Any, AnyStr, Callable, Collection, Dict, Hashable, Iterator, List, Mapping, NewType, Optional, Sequence, Tuple, TypeVar, Union
  from pandas.api.types import is_categorical_dtype, is_numeric_dtype
label_desc: Use image node_id 1 to create a new FillMissing object from inherited base classes: TabularProc with example: obj = FillMissing(cat_names, cont_names, fill_strategy, add_col, fill_val)