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Semi-Supervised Classification with Informative Missing Labels in Weibull Mixture Models

Wu, Jinran et al.
arXiv (All) · Papers
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machine-learning
We consider semi-supervised classification from a partially classified sample arising from a two-component Weibull mixture. The feature is observed for all data, whereas some class labels are missing. The probability of a missing label is modelled as a function of classification uncertainty, giving
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