code: def fit(self, x):
      self.lbl.fit(x)  # list(x.values))
      if self._try_to_fit_numeric:
          logger.debug("Try to fit numeric in LabelEncoder")
          try:
              arr = {Decimal(c): c for c in self.lbl.classes_}
              sorted_arr = dict(sorted(arr.items()))
              self.lbl.classes_ = np.array(
                  list(sorted_arr.values()),
                  dtype=self.lbl.classes_.dtype,
              )
          except Exception as e:
              pass
  
file_path: mljar-supervised/supervised/preprocessing/label_encoder.py
imports: import copy
  import logging
  from decimal import Decimal
  import numpy
  from sklearn import preprocessing
  from supervised.utils.config import LOG_LEVEL
label_desc: Use image node_id 2 for calling the LabelEncoder obj's underlying member method code with example usage: obj.fit(x) without return types