Fuzzy Multi-Sphere Support Vector Data Description

International Conference on Fuzzy Systems (FUZZ-IEEE)

Research output: A Conference proceeding or a Chapter in BookConference contribution

4 Citations (Scopus)
1 Downloads (Pure)

Abstract

Multi-sphere Support Vector Data Description (MS-SVDD) has been proposed in our previous work. MS-SVDD aims to build a set of spherically shaped boundaries that provide a better data description to the normal dataset and an iterative learning algorithm that determines the set of spherically shaped boundaries. MS-SVDD could improve classification rate for one-class classification problems comparing with SVDD. However MS-SVDD requires a small abnormal data set to build the spherically shaped boundaries for the normal data set. In this paper, we propose a new fuzzy MS-SVDD that can be used when only the normal data set is available. Experimental results on 14 well-known datasets and a comparison between fuzzy MS-SVDD and SVDD are also presented
Original languageEnglish
Title of host publication2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
EditorsHussein Abbass
Place of PublicationNew York
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1956-1960
Number of pages5
ISBN (Print)9781467315050
DOIs
Publication statusPublished - 2012
EventWCCI 2012 IEEE World Congress on Computational Intelligence - Brisbane, Brisbane, Australia
Duration: 10 Jun 201215 Jun 2012

Conference

ConferenceWCCI 2012 IEEE World Congress on Computational Intelligence
CountryAustralia
CityBrisbane
Period10/06/1215/06/12

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Cite this

Le, T., Tran, D., Ma, W., & Sharma, D. (2012). Fuzzy Multi-Sphere Support Vector Data Description: International Conference on Fuzzy Systems (FUZZ-IEEE). In H. Abbass (Ed.), 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (pp. 1956-1960). New York: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/FUZZ-IEEE.2012.6251336