code: def _preprocess_values(self, Y):
          
          Y_prep = Y.copy()
          Y1 = Y[Y.flatten()==1].size
          Y2 = Y[Y.flatten()==0].size
          assert Y1 + Y2 == Y.size, 'Bernoulli likelihood is meant to be used only with outputs in {0, 1}.'
          Y_prep[Y.flatten() == 0] = -1
          return Y_prep
docs: Check if the values of the observations correspond to the values
          assumed by the likelihood function.
  
          ..Note:: Binary classification algorithm works better with classes {-1, 1}