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: Helper function to make classifications for a condition
  in a rule
docstr_tok: ["Helper","function","to","make","classifications","for","a","condition","in","a","rule"]
code: def _condition_classify(self, X, condition):
      """
      Helper function to make classifications for a condition
      in a rule
      """
  
      logic = "X[:, {}] {} {}".format(
          condition["feature"],
          condition["operator"],
          condition["pivot"],
      )
  
      output = np.where(eval(logic))
      return output[0]
  
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 3 for calling the SlipperBaseEstimator obj's underlying member method code with example usage: obj._condition_classify(X, condition) and returns: output