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Table 1 Properties of multi-annotator algorithms.

From: Learning by aggregating experts and filtering novices: a solution to crowdsourcing problems in bioinformatics

Algorithms Unsupervised? Integrate labels globally? Data dependent? Filter novice annotation?
MV Y N N N
MAP-ML Y Y N N
GMM-MAPML Y Y Y N
AEFN Y Y Y Y
  1. The comparisons of properties of multi-annotator algorithms are shown. 'Y' denotes that the algorithm has the property; 'N' denotes that the algorithm doesn't have the property.
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