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Active Learning of Multi-class Classification Models from Ordered Class Sets

In this paper, we study the problem of learning multi-class classification models from a limited set of labeled examples obtained from human annotator. We propose a new machine learning framework that learns multi-class classification models from ordered class sets the annotator may use to express n...

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Sparad:
Bibliografiska uppgifter
I publikationen:Proc AAAI Conf Artif Intell
Huvudupphovsmän: Xue, Yanbing, Hauskrecht, Milos
Materialtyp: Artigo
Språk:Inglês
Publicerad: 2019
Ämnen:
Länkar:https://ncbi.nlm.nih.gov/pmc/articles/PMC6867686/
https://ncbi.nlm.nih.gov/pubmed/31750011
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