code: def __init__(self, combination=()):
      self.scaler = MinMaxScaler()
      self.abs_mean = None
      self.combination = (
          combination  # tuple with values in grouped-by columns
      )
      self.output_size = 1
  
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 MinMaxNormalizer object  with example: obj = MinMaxNormalizer(combination)