code: def _classes(self):
      # Returns the unique classes based on the fitted model
      if hasattr(self.model, "classes_"):
          return self.model.classes_
      else:
          return None
  
imports: import logging
  import os
  import numpy
  import sklearn
  from sklearn.base import ClassifierMixin, RegressorMixin
  from sklearn.model_selection import train_test_split
  from sklearn.neighbors import KNeighborsClassifier, KNeighborsRegressor
  from supervised.algorithms.algorithm import BaseAlgorithm
  from supervised.algorithms.registry import BINARY_CLASSIFICATION, MULTICLASS_CLASSIFICATION, REGRESSION, AlgorithmsRegistry
  from supervised.algorithms.sklearn import SklearnAlgorithm
  from supervised.utils.config import LOG_LEVEL
label_desc: Use image node_id 4 for calling the KNNFit obj's underlying member method code with example usage: obj._classes() and returns: self, None