Citing the sklearn implementation of the stochastic gradient descent regressor - you would have to use the hinge loss
https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDClassifier.html 87
parameter: loss - Defaults to ‘hinge’, which gives a linear SVM.
SVM 0-1 loss has infinite slope at 0, the hinge loss can be seen as a differentiable approximation to it.
For further details see

  
      math.stackexchange.com
  
  
      
    
  

  Why "hinge" loss is equivalent to 0-1 loss in SVM? 75



  statistics, self-learning, machine-learning



  asked by
  
  
    Tina
  
  on 09:23PM - 11 Mar 13 UTC