Direct Uncertainty Prediction with Applications to Healthcare
arXiv: Learning, Volume abs/1807.01771, 2018.
Large labeled datasets for supervised learning are frequently constructed by assigning each instance to multiple human evaluators, and this leads to disagreement in the labels associated with a single instance. Here we consider the question of predicting the level of disagreement for a given instance, and we find an interesting phenomenon...More
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