NEATER: Filtering of over-sampled data using non-cooperative game theory

B. A. Almogahed, I. A. Kakadiaris

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

6 Scopus citations

Abstract

We present a method for the filtering of over-sampled data using non-cooperative game theory (NEATER) to address the imbalanced data problem using game theory. Specifically, the problem is formulated as a non-cooperative game where all the data are players and the goal is to uniformly and consistently label all of the synthetic data created by any over-sampling technique. We present extensive experimental results which demonstrate the advantages of our method.

Original languageEnglish (US)
Title of host publicationProceedings - International Conference on Pattern Recognition
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1371-1376
Number of pages6
ISBN (Electronic)9781479952083
DOIs
StatePublished - Dec 4 2014
Event22nd International Conference on Pattern Recognition, ICPR 2014 - Stockholm, Sweden
Duration: Aug 24 2014Aug 28 2014

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

Conference

Conference22nd International Conference on Pattern Recognition, ICPR 2014
Country/TerritorySweden
CityStockholm
Period8/24/148/28/14

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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