A new fuzzy membership computation method for fuzzy support vector machines

Trung Le; Dat Tran; Wanli Ma; Dharmendra Sharma

doi:10.1109/ICCE.2010.5670701

A new fuzzy membership computation method for fuzzy support vector machines

Trung Le
, Dat Tran
, Wanli Ma
, Dharmendra Sharma

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

6 Citations (Scopus)

Abstract

Support vector machine (SVM) considers all data points with the same importance in classification problems, therefore SVM is very sensitive to noisy data or outliers. Current fuzzy approach to two-class SVM introduces a fuzzy membership to each data point in order to reduce the sensitivity of less important data, however computing fuzzy memberships is still a challenge. It has been found that the performance of fuzzy SVM highly depends on the computation of fuzzy memberships, hence in this paper, we propose a new method to compute fuzzy memberships and we also extend the fuzzy approach for two-class SVM to one-class SVM. Experiments performed on a number of popular data sets to evaluation the proposed fuzzy SVMs show promising classification results.

Original language	English
Title of host publication	International Conference on Communications and Electronics 2010
Place of Publication	Piscataway NJ USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	153-157
Number of pages	5
ISBN (Print)	9781424470587
DOIs	https://doi.org/10.1109/ICCE.2010.5670701
Publication status	Published - 2010
Externally published	Yes
Event	International Conference on Communications and Electronics (HUT-ICCE) 2010 - Nha Trang, Vietnam Duration: 11 Aug 2010 → 13 Aug 2010 Conference number: 3rd https://ieeexplore.ieee.org/xpl/conhome/5661636/proceeding (Proceedings)

Conference

Conference	International Conference on Communications and Electronics (HUT-ICCE) 2010
Abbreviated title	ICCE 2010
Country/Territory	Vietnam
City	Nha Trang
Period	11/08/10 → 13/08/10
Internet address	https://ieeexplore.ieee.org/xpl/conhome/5661636/proceeding (Proceedings)

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10.1109/ICCE.2010.5670701

Cite this

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title = "A new fuzzy membership computation method for fuzzy support vector machines",

abstract = "Support vector machine (SVM) considers all data points with the same importance in classification problems, therefore SVM is very sensitive to noisy data or outliers. Current fuzzy approach to two-class SVM introduces a fuzzy membership to each data point in order to reduce the sensitivity of less important data, however computing fuzzy memberships is still a challenge. It has been found that the performance of fuzzy SVM highly depends on the computation of fuzzy memberships, hence in this paper, we propose a new method to compute fuzzy memberships and we also extend the fuzzy approach for two-class SVM to one-class SVM. Experiments performed on a number of popular data sets to evaluation the proposed fuzzy SVMs show promising classification results.",

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

year = "2010",

doi = "10.1109/ICCE.2010.5670701",

language = "English",

isbn = "9781424470587",

pages = "153--157",

booktitle = "International Conference on Communications and Electronics 2010",

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

address = "United States of America",

note = "International Conference on Communications and Electronics (HUT-ICCE) 2010, ICCE 2010 ; Conference date: 11-08-2010 Through 13-08-2010",

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}

Le, T, Tran, D, Ma, W & Sharma, D 2010, A new fuzzy membership computation method for fuzzy support vector machines. in International Conference on Communications and Electronics 2010., 5670701, IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, pp. 153-157, International Conference on Communications and Electronics (HUT-ICCE) 2010, Nha Trang, Vietnam, 11/08/10. https://doi.org/10.1109/ICCE.2010.5670701

A new fuzzy membership computation method for fuzzy support vector machines. / Le, Trung; Tran, Dat; Ma, Wanli et al.
International Conference on Communications and Electronics 2010. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 2010. p. 153-157 5670701.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

TY - GEN

T1 - A new fuzzy membership computation method for fuzzy support vector machines

AU - Le, Trung

AU - Tran, Dat

AU - Ma, Wanli

AU - Sharma, Dharmendra

N1 - Conference code: 3rd

PY - 2010

Y1 - 2010

N2 - Support vector machine (SVM) considers all data points with the same importance in classification problems, therefore SVM is very sensitive to noisy data or outliers. Current fuzzy approach to two-class SVM introduces a fuzzy membership to each data point in order to reduce the sensitivity of less important data, however computing fuzzy memberships is still a challenge. It has been found that the performance of fuzzy SVM highly depends on the computation of fuzzy memberships, hence in this paper, we propose a new method to compute fuzzy memberships and we also extend the fuzzy approach for two-class SVM to one-class SVM. Experiments performed on a number of popular data sets to evaluation the proposed fuzzy SVMs show promising classification results.

AB - Support vector machine (SVM) considers all data points with the same importance in classification problems, therefore SVM is very sensitive to noisy data or outliers. Current fuzzy approach to two-class SVM introduces a fuzzy membership to each data point in order to reduce the sensitivity of less important data, however computing fuzzy memberships is still a challenge. It has been found that the performance of fuzzy SVM highly depends on the computation of fuzzy memberships, hence in this paper, we propose a new method to compute fuzzy memberships and we also extend the fuzzy approach for two-class SVM to one-class SVM. Experiments performed on a number of popular data sets to evaluation the proposed fuzzy SVMs show promising classification results.

UR - https://www.scopus.com/pages/publications/78751533817

U2 - 10.1109/ICCE.2010.5670701

DO - 10.1109/ICCE.2010.5670701

M3 - Conference Paper

AN - SCOPUS:78751533817

SN - 9781424470587

SP - 153

EP - 157

BT - International Conference on Communications and Electronics 2010

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Piscataway NJ USA

T2 - International Conference on Communications and Electronics (HUT-ICCE) 2010

Y2 - 11 August 2010 through 13 August 2010

ER -

A new fuzzy membership computation method for fuzzy support vector machines

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