code: def fit(self, X, y, sample_weight=None, check_input=True):
      super()._fit(
          X,
          y,
          sample_weight=sample_weight,
          check_input=check_input,
      )
      return self
  
imports: from abc import ABCMeta, abstractmethod
  from ..base import BaseEstimator, ClassifierMixin, MultiOutputMixin
  import copy
  from ._criterion import Gini, Criterion
  from ._splitter import BestSplitter, Splitter
  from ._tree import DepthFirstTreeBuilder, Tree
  import ivy
  import numbers
label_desc: Use image node_id 2 for calling the DecisionTreeClassifier obj's underlying member method code with example usage: obj.fit(X, y, sample_weight, check_input) and returns: self