function classify_multiclass(x, models): # one-vs-rest

   scores = {label: model.score(x) for label, model in models}
   return argmax(scores) # the label whose model is most confident

 # or, with a single softmax model:
 function softmax(scores):
   exp_scores = [exp(s) for s in scores]

   return [e / sum(exp_scores) for e in exp_scores] # a probability per class
