class_docstr: Vowpal Wabbit Scikit-learn Base Estimator wrapper
class_docstr_tok: ["Vowpal","Wabbit","Scikit-learn","Base","Estimator","wrapper"]
docstr: Returns intercept weight for model
  
  Returns:
      int: intercept value. 0 if no constant
code: def get_intercept(self):
      """Returns intercept weight for model
  
      Returns:
          int: intercept value. 0 if no constant
      """
  
      return self.get_vw().get_weight(CONSTANT_HASH)
  
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 9 for calling the VW obj's underlying member method code with example usage: obj.get_intercept() and returns: self