Submitted by groman434 t3_103694n in MachineLearning
_Arsenie_Boca_ t1_j2xonjk wrote
Yes, I believe there are 2 factors playing a role here:
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Models could potentially correct some errors of the human labeler using their generalization power, provided that the model is not overfitted.
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You should differentiate between outperforming a human and outperforming humans. Labels usually represent the collective knowledge of a number of people not just one.
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