class_docstr: An estimator that supports building rules as described in
  A Simple, Fast, and Effective Rule Learner (1999). Intended to be used
  as part of the SlipperRulesClassifier.
class_docstr_tok: ["An","estimator","that","supports","building","rules","as","described","in","A","Simple",",","Fast",",","and","Effective","Rule","Learner","(","1999",")",".","Intended","to","be","used","as","part","of","the","SlipperRulesClassifier","."]
docstr: Compare output of eq 5 between learned rule and default rule
  return rule that minimizes eq 5
docstr_tok: ["Compare","output","of","eq","5","between","learned","rule","and","default","rule","return","rule","that","minimizes","eq","5"]
code: def _set_rule_or_default(self, X, y, learned_rule):
      """
      Compare output of eq 5 between learned rule and default rule
      return rule that minimizes eq 5
      """
  
      rules = [self._make_default_rule(X, y), learned_rule]
      scores = [self._eq_5(X, y, rule) for rule in rules]
      self.rule = rules[scores.index(min(scores))]
  
imports: import random
  import numpy
  from sklearn.base import BaseEstimator, ClassifierMixin
  from sklearn.model_selection import train_test_split
  from imodels.util.arguments import check_fit_arguments
label_desc: Use image node_id 14 for calling the SlipperBaseEstimator obj's underlying member method code with example usage: obj._set_rule_or_default(X, y, learned_rule) without return types