class_docstr: Shallow Decision Tree (low depth).
  
  Currently wrapper around DecisionTreeClassifier or DecisionTreeRegressor in scikit-learn.
  To keep the tree shallow, max depth is defaulted to 3.
  
  https://github.com/scikit-learn/scikit-learn
class_docstr_tok: ["Shallow","Decision","Tree","(","low","depth",")",".","Currently","wrapper","around","DecisionTreeClassifier","or","DecisionTreeRegressor","in","scikit-learn",".","To","keep","the","tree","shallow",",","max","depth","is","defaulted","to","3.","https",":","\/\/github.com\/scikit-learn\/scikit-learn"]
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.
      """
      self.feature_names = feature_names
      self.feature_types = feature_types
      self.max_depth = max_depth
      self.kwargs = 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 BaseShallowDecisionTree object  with example: obj = BaseShallowDecisionTree(feature_names, feature_types, max_depth)