class_docstr: Encodes missing values for both numerical and categorical features.
  
  Several strategies are possible in each case.
  
  Parameters
  ----------
  numerical_strategy : str or float or int. default = "mean"
      The strategy to encode NA for numerical features.
      Available strategies = "mean", "median",
      "most_frequent" or a float/int value
  
  categorical_strategy : str, default = '<NULL>'
      The strategy to encode NA for categorical features.
      Available strategies = a string or "most_frequent"
docstr: Get parameters of a NA_encoder object.
code: def get_params(self, deep=True):
      """Get parameters of a NA_encoder object."""
      return {
          "numerical_strategy": self.numerical_strategy,
          "categorical_strategy": self.categorical_strategy,
      }
  
file_path: MLBox/mlbox/encoding/na_encoder.py
imports: import pandas
  import warnings
  from sklearn.impute import SimpleImputer
label_desc: Use image node_id 2 for calling the NA_encoder obj's underlying member method code with example usage: obj.get_params(deep) and returns: dict