code: def __init__(self, results_path=None, model_name=None, k_fold=None):
      self._new_features = []
      self._input_columns = []
      self._error = None
      self._kmeans = None
      self._scale = None
      self._model_name = model_name
      self._k_fold = k_fold
  
      if results_path is not None:
          self._result_file = os.path.join(
              self._model_name, f"kmeans_fold_{k_fold}.joblib"
          )
          self._result_path = os.path.join(
              results_path, self._result_file
          )
  
file_path: mljar-supervised/supervised/preprocessing/kmeans_transformer.py
imports: import datetime
  import json
  import os
  import time
  import joblib
  import numpy
  import pandas
  from sklearn.cluster import MiniBatchKMeans
  from sklearn.preprocessing import StandardScaler
  from supervised.exceptions import AutoMLException
label_desc: Use image node_id 1 to create a new KMeansTransformer object from inherited base classes: object with example: obj = KMeansTransformer(results_path, model_name, k_fold)