class_docstr: Vowpal Wabbit Scikit-learn Base Estimator wrapper
class_docstr_tok: ["Vowpal","Wabbit","Scikit-learn","Base","Estimator","wrapper"]
docstr: Returns coefficient weights as ordered sparse matrix
  
  Returns:
      sparse matrix: coefficient weights for model
code: def get_coefs(self):
      """Returns coefficient weights as ordered sparse matrix
  
      Returns:
          sparse matrix: coefficient weights for model
      """
  
      model = self.get_vw()
      return csr_matrix(
          [model.get_weight(i) for i in range(model.num_weights())]
      )
  
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 7 for calling the VW obj's underlying member method code with example usage: obj.get_coefs() and returns: csr_matrix