code: def __init__(self, encoder_class="one_hot"):
      self.encoder_class = encoder_class
      if encoder_class == "one_hot":
          self.scaler = OneHotEncoder(
              sparse=False, handle_unknown="ignore"
          )
      else:
          self.scaler = OrdinalEncoder()
  
      self.unk = "<UNK>"
  
file_path: lightwood/lightwood/encoder/helpers.py
imports: import torch
  import numpy
  from sklearn.preprocessing import MinMaxScaler, OneHotEncoder, OrdinalEncoder
label_desc: Use image node_id 1 to create a new CatNormalizer object  with example: obj = CatNormalizer(encoder_class)