code: def fit(
      self, X, y=None, feature_names=None, undiscretized_features=[]
  ):
      self.undiscretized_features = undiscretized_features
      super().fit(X, y, feature_names=feature_names)
      return self
  
file_path: imodels/imodels/rule_set/fplasso.py
imports: from typing import List
  import pandas
  from sklearn.base import ClassifierMixin, RegressorMixin
  from imodels.rule_set.rule_fit import RuleFit
  from imodels.util.convert import itemsets_to_rules
  from imodels.util.extract import extract_fpgrowth
label_desc: Use image node_id 2 for calling the FPLasso obj's underlying member method code with example usage: obj.fit(X, y, feature_names, undiscretized_features) and returns: self