Active Learning with Unbalanced Classes and Example-Generation Queries

HCOMP, pp. 98-107, 2018.

Cited by: 5|Bibtex|Views98
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Other Links: dblp.uni-trier.de|academic.microsoft.com

Abstract:

Machine learning in real-world high-skew domains is difficult, because traditional strategies for crowdsourcing labeled training examples are ineffective at locating the scarce minority-class examples. For example, both random sampling and traditional active learning (which reduces to random sampling when just starting) will most likely r...More

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