class_docstr: Ruleset estimator based on Boolean Rules with Column Generation.
  
  Operates according to an scikit-learn interface with a few additional methods.
class_docstr_tok: ["Ruleset","estimator","based","on","Boolean","Rules","with","Column","Generation",".","Operates","according","to","an","scikit-learn","interface","with","a","few","additional","methods","."]
docstr: Initialize rule set estimator and feature binarizer.
docstr_tok: ["Initialize","rule","set","estimator","and","feature","binarizer","."]
code: def init_estimator_(self):
      """Initialize rule set estimator and feature binarizer."""
      self.M = OverlapBooleanRule(
          lambda0=self.lambda0, lambda1=self.lambda1, **self.kwargs
      )
  
      self.FeatureBinarizer = FeatureBinarizer(
          negations=self.negations,
          colCateg=self.cat_cols,
          numThresh=self.num_thresh,
          threshOverride=self.thresh_override,
      )
  
file_path: dowhy/dowhy/causal_refuters/overrule/ruleset.py
imports: from typing import Callable, Dict, List, Optional
  import numpy
  import pandas
  from .BCS.load_process_data_BCS import FeatureBinarizer
  from .BCS.overlap_boolean_rule import OverlapBooleanRule
  from .utils import rule_str, sample_reference
label_desc: Use image node_id 4 for calling the BCSRulesetEstimator obj's underlying member method code with example usage: obj.init_estimator_() without return types