docstr: An estimator that supports building rules as described in
  A Simple, Fast, and Effective Rule Learner (1999).
  Parameters
  ----------
  n_estimators
docstr_tok: ["An","estimator","that","supports","building","rules","as","described","in","A","Simple",",","Fast",",","and","Effective","Rule","Learner","(","1999",")",".","Parameters","--","--","--","--","--","n_estimators"]
code: def __init__(self, n_estimators=10, **kwargs):
      """
      An estimator that supports building rules as described in
      A Simple, Fast, and Effective Rule Learner (1999).
      Parameters
      ----------
      n_estimators
      """
      super().__init__(
          estimator=SlipperBaseEstimator(),
          n_estimators=n_estimators,
          **kwargs,
      )
  
imports: from imodels.rule_set.boosted_rules import BoostedRulesClassifier
  from imodels.rule_set.slipper_util import SlipperBaseEstimator
label_desc: Use image node_id 1 to create a new SlipperClassifier object from inherited base classes: BoostedRulesClassifier with example: obj = SlipperClassifier(n_estimators)