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iftrue>1andpred>1:
continueifpred>1: # pred == 2 and true < 2, miss predictedfn+=1eliftrue==pred: # correctly predictedtp+=1else: # (true == 2 and pred < 2) or true != pred, wrongly predictedfp+=1
The text was updated successfully, but these errors were encountered:
https://github.com/csJd/bdci_ei/blob/eee334380e55b5a900281f16b4fdec0898767066/term_weighting_model/classifiers.py#L71
Which should be following
The text was updated successfully, but these errors were encountered: