class_docstr: Vowpal Wabbit Scikit-learn Base Estimator wrapper
class_docstr_tok: ["Vowpal","Wabbit","Scikit-learn","Base","Estimator","wrapper"]
docstr: This destroys and recreates the Vowpal Wabbit model with updated parameters
  any parameters not provided will remain as they are currently
code: def set_params(self, **kwargs):
      """This destroys and recreates the Vowpal Wabbit model with updated parameters
      any parameters not provided will remain as they are currently"""
  
      params = self.get_params()
      params.update(kwargs)
      private_params = dict()
      for k, v in params.copy().items():
          if k.endswith("_"):
              private_params[k] = v
              params.pop(k)
      self.__init__(**params)
      for k, v in private_params.items():
          setattr(self, k, v)
      self.vw_ = None
      return self
  
imports: import io
  import os
  import re
  from tempfile import NamedTemporaryFile
  from typing import Dict
  import numpy
  from scipy.sparse import csr_matrix
  from scipy.special import logit
  from sklearn.exceptions import NotFittedError
  from sklearn.base import BaseEstimator, RegressorMixin
  from sklearn.utils.extmath import log_logistic
  from sklearn.linear_model import LogisticRegression
  from sklearn.datasets import dump_svmlight_file
  from sklearn.utils import check_array, check_X_y, shuffle
  from vowpalwabbit import Workspace
label_desc: Use image node_id 6 for calling the VW obj's underlying member method code with example usage: obj.set_params() and returns: self