class_docstr: Classification tree with shallow depth.
class_docstr_tok: ["Classification","tree","with","shallow","depth","."]
docstr: Initializes tree with low depth.
  
  Args:
      feature_names: List of feature names.
      feature_types: List of feature types.
      max_depth: Max depth of tree.
      **kwargs: Kwargs sent to __init__() method of tree.
docstr_tok: ["Initializes","tree","with","low","depth",".","Args",":","feature_names",":","List","of","feature","names",".","feature_types",":","List","of","feature","types",".","max_depth",":","Max","depth","of","tree",".","*","*","kwargs",":","Kwargs","sent","to","__init__","(",")","method","of","tree","."]
code: def __init__(
      self,
      feature_names=None,
      feature_types=None,
      max_depth=3,
      **kwargs,
  ):
      """Initializes tree with low depth.
  
      Args:
          feature_names: List of feature names.
          feature_types: List of feature types.
          max_depth: Max depth of tree.
          **kwargs: Kwargs sent to __init__() method of tree.
      """
      super().__init__(
          feature_names=feature_names,
          feature_types=feature_types,
          max_depth=max_depth,
          **kwargs,
      )
  
imports: from ..api.base import ExplainerMixin, ExplanationMixin
  from ..utils._explanation import gen_name_from_class, gen_local_selector, gen_global_selector, gen_perf_dicts
  from sklearn.base import ClassifierMixin, RegressorMixin
  from sklearn.tree import DecisionTreeClassifier
  from sklearn.tree import DecisionTreeRegressor
  from sklearn.base import is_classifier
  from sklearn.utils.validation import check_is_fitted
  import numpy
  from abc import abstractmethod
  from sklearn.tree import _tree
  from copy import deepcopy
  from ..utils._clean_x import preclean_X
  from ..utils._clean_simple import clean_dimensions, typify_classification
  from ..utils._unify_data import unify_data
  import logging
label_desc: Use image node_id 1 to create a new ClassificationTree object from inherited base classes: BaseShallowDecisionTree, ClassifierMixin, ExplainerMixin with example: obj = ClassificationTree(feature_names, feature_types, max_depth)