code: def __init__(
      self,
      *,
      criterion="gini",
      splitter="best",
      max_depth=None,
      min_samples_split=2,
      min_samples_leaf=1,
      min_weight_fraction_leaf=0.0,
      max_features=None,
      random_state=None,
      max_leaf_nodes=None,
      min_impurity_decrease=0.0,
      class_weight=None,
      ccp_alpha=0.0,
  ):
      super().__init__(
          criterion=criterion,
          splitter=splitter,
          max_depth=max_depth,
          min_samples_split=min_samples_split,
          min_samples_leaf=min_samples_leaf,
          min_weight_fraction_leaf=min_weight_fraction_leaf,
          max_features=max_features,
          max_leaf_nodes=max_leaf_nodes,
          class_weight=class_weight,
          random_state=random_state,
          min_impurity_decrease=min_impurity_decrease,
          ccp_alpha=ccp_alpha,
      )
  
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 1 to create a new DecisionTreeClassifier object from inherited base classes: ClassifierMixin, BaseDecisionTree with example: obj = DecisionTreeClassifier()