class_docstr: A class for learning a staircase decision tree.
  
  Args:
      domain: The number of points in the domain.
      n_classes: The number of classes.
class_docstr_tok: ["A","class","for","learning","a","staircase","decision","tree",".","Args",":","domain",":","The","number","of","points","in","the","domain",".","n_classes",":","The","number","of","classes","."]
code: def score(self):
      try:
          return gini_impurity(
              self.thresholds, self._data, self._labels
          ) / len(self._data)
      except AttributeError:
          return np.inf
  
imports: from collections import deque
  import operator
  import itertools
  from typing import Optional, List, Tuple
  import numpy
  import warnings
label_desc: Use image node_id 4 for calling the Staircase obj's underlying member method code with example usage: obj.score() and returns: unknown, np