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: Calculate learner sample weight
  in paper this is C_R, which is confidence of learner
docstr_tok: ["Calculate","learner","sample","weight","in","paper","this","is","C_R",",","which","is","confidence","of","learner"]
code: def _sample_weight(self, plus, minus):
      """Calculate learner sample weight
      in paper this is C_R, which is confidence of learner
      """
      return 0.5 * np.log(
          (plus + (1 / (2 * len(self.D))))
          / (minus + 1 / (2 * len(self.D)))
      )
  
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 7 for calling the SlipperBaseEstimator obj's underlying member method code with example usage: obj._sample_weight(plus, minus) and returns: unknown