Fuzzy Multi-Sphere Support Vector Data Description: International Conference on Fuzzy Systems (FUZZ-IEEE)

Trung Le; Dat Tran; Wanli Ma; Dharmendra Sharma

doi:10.1109/FUZZ-IEEE.2012.6251336

Fuzzy Multi-Sphere Support Vector Data Description: International Conference on Fuzzy Systems (FUZZ-IEEE)

Trung Le, Dat Tran, Wanli Ma, Dharmendra Sharma

Information Systems

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

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 language	English
Title of host publication	2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Editors	Hussein Abbass
Place of Publication	New York
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	1956-1960
Number of pages	5
ISBN (Print)	9781467315050
DOIs	https://doi.org/10.1109/FUZZ-IEEE.2012.6251336
Publication status	Published - 2012
Event	WCCI 2012 IEEE World Congress on Computational Intelligence - Brisbane, Brisbane, Australia Duration: 10 Jun 2012 → 15 Jun 2012

Conference

Conference	WCCI 2012 IEEE World Congress on Computational Intelligence
Country/Territory	Australia
City	Brisbane
Period	10/06/12 → 15/06/12

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10.1109/FUZZ-IEEE.2012.6251336

Cite this

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title = "Fuzzy Multi-Sphere Support Vector Data Description: International Conference on Fuzzy Systems (FUZZ-IEEE)",

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",

keywords = "Support Vector Data Description",

author = "Trung Le and Dat Tran and Wanli Ma and Dharmendra Sharma",

year = "2012",

doi = "10.1109/FUZZ-IEEE.2012.6251336",

language = "English",

isbn = "9781467315050",

pages = "1956--1960",

editor = "Hussein Abbass",

booktitle = "2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States",

note = "WCCI 2012 IEEE World Congress on Computational Intelligence ; Conference date: 10-06-2012 Through 15-06-2012",

}

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). IEEE, Institute of Electrical and Electronics Engineers, New York, pp. 1956-1960, WCCI 2012 IEEE World Congress on Computational Intelligence, Brisbane, Queensland, Australia, 10/06/12. https://doi.org/10.1109/FUZZ-IEEE.2012.6251336

Fuzzy Multi-Sphere Support Vector Data Description: International Conference on Fuzzy Systems (FUZZ-IEEE). / Le, Trung; Tran, Dat; Ma, Wanli et al.
2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). ed. / Hussein Abbass. New York: IEEE, Institute of Electrical and Electronics Engineers, 2012. p. 1956-1960.

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

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T1 - Fuzzy Multi-Sphere Support Vector Data Description

T2 - WCCI 2012 IEEE World Congress on Computational Intelligence

AU - Le, Trung

AU - Tran, Dat

AU - Ma, Wanli

AU - Sharma, Dharmendra

PY - 2012

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N2 - 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

AB - 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

KW - Support Vector Data Description

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M3 - Conference contribution

SN - 9781467315050

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EP - 1960

BT - 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

A2 - Abbass, Hussein

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - New York

Y2 - 10 June 2012 through 15 June 2012

ER -

Fuzzy Multi-Sphere Support Vector Data Description: International Conference on Fuzzy Systems (FUZZ-IEEE)

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