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Supervised Learning from Multiple Experts: Whom to Trust When Everyone Lies a Bit
Published on 2009-08-264369 Views
We describe a probabilistic approach for supervised learning when we have multiple experts/annotators providing (possibly noisy) labels but no absolute gold standard. The proposed algorithm evaluates
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