Density-based evolutionary outlier detection

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

2 Scopus citations

Abstract

A novel density-based distance measure and an outlier detection method using evolutionary search are presented in this paper. A fitness function based on nearest neighbor distances is proposed and the genetic recombination operators are designed to achieve a balance of exploration and exploitation in the nearest neighborhood space. The methodology is tested on datasets of varying sizes (small to moderate) and dimensionalities and performance is compared to existing evolutionary methods for outlier detection. Copyright is held by the author/owner(s).

Original languageEnglish (US)
Title of host publicationGECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation Companion
Pages651-652
Number of pages2
DOIs
StatePublished - Aug 20 2012
Event14th International Conference on Genetic and Evolutionary Computation, GECCO'12 - Philadelphia, PA, United States
Duration: Jul 7 2012Jul 11 2012

Publication series

NameGECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation Companion

Other

Other14th International Conference on Genetic and Evolutionary Computation, GECCO'12
CountryUnited States
CityPhiladelphia, PA
Period7/7/127/11/12

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics

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  • Cite this

    Banerjee, A. (2012). Density-based evolutionary outlier detection. In GECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation Companion (pp. 651-652). (GECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation Companion). https://doi.org/10.1145/2330784.2330904