EUS SVMs: Ensemble of under-sampled SVMs for data imbalance problems

Pilsung Kang, Sungzoon Cho

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

102 Citations (Scopus)

Abstract

Data imbalance occurs when the number of patterns from a class is much larger than that from the other class. It often degenerates the classification performance. In this paper, we propose an Ensemble of Under-Sampled SVMs or EUS SVMs. We applied the proposed method to two synthetic and six real data sets and we found that it outperformed other methods, especially when the number of patterns belonging to the minority class is very small.

Original languageEnglish
Title of host publicationNeural Information Processing - 13th International Conference, ICONIP 2006, Proceedings
PublisherSpringer Verlag
Pages837-846
Number of pages10
ISBN (Print)3540464794, 9783540464792
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event13th International Conference on Neural Information Processing, ICONIP 2006 - Hong Kong, China
Duration: 2006 Oct 32006 Oct 6

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4232 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other13th International Conference on Neural Information Processing, ICONIP 2006
CountryChina
CityHong Kong
Period06/10/306/10/6

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Kang, P., & Cho, S. (2006). EUS SVMs: Ensemble of under-sampled SVMs for data imbalance problems. In Neural Information Processing - 13th International Conference, ICONIP 2006, Proceedings (pp. 837-846). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4232 LNCS). Springer Verlag. https://doi.org/10.1007/11893028_93