Active learning for class imbalance problem

Seyda Ertekin, Jian Huang, C. Lee Giles

Research output: Chapter in Book/Report/Conference proceedingConference contribution

98 Scopus citations

Abstract

The class imbalance problem has been known to hinder the learning performance of classification algorithms. Various real-world classification tasks such as text categorization suffer from this phenomenon. We demonstrate that active learning is capable of solving the problem.

Original languageEnglish (US)
Title of host publicationProceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'07
Pages823-824
Number of pages2
DOIs
StatePublished - Nov 30 2007
Event30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'07 - Amsterdam, Netherlands
Duration: Jul 23 2007Jul 27 2007

Publication series

NameProceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'07

Other

Other30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'07
CountryNetherlands
CityAmsterdam
Period7/23/077/27/07

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All Science Journal Classification (ASJC) codes

  • Information Systems
  • Software
  • Applied Mathematics

Cite this

Ertekin, S., Huang, J., & Giles, C. L. (2007). Active learning for class imbalance problem. In Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'07 (pp. 823-824). (Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR'07). https://doi.org/10.1145/1277741.1277927