Nonlinear feature extraction using evolutionary algorithm

E.K. TANG; Ponnuthurai Nagaratnan SUGANTHAN; Xin YAO

doi:10.1007/978-3-540-30499-9_157

Nonlinear feature extraction using evolutionary algorithm

E.K. TANG, Ponnuthurai Nagaratnan SUGANTHAN, Xin YAO

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

2 Citations (Scopus)

Abstract

We propose a method of nonlinear feature extraction for 2-class problems. A simple sigmoid function is used to extract features that are negatively correlated to each other. To evaluate the effectiveness of the proposed method, we employ linear and non-linear support vector machines to classify using the extracted feature sets and the original feature sets. Comparison on 4 datasets shows that our method is effective for nonlinear feature extraction. © Springer-Verlag Berlin Heidelberg 2004.

Original language	English
Title of host publication	Neural Information Processing : 11th International Conference, ICONIP 2004 Calcutta, India, November 22–25, 2004 Proceedings
Editors	Nikhil Ranjan PAL, Nik KASABOV, Rajani K. MUDI, Srimanta PAL, Swapan Kumar PARUI
Publisher	Springer Berlin Heidelberg
Pages	1014-1019
Number of pages	6
ISBN (Electronic)	9783540304999
ISBN (Print)	9783540239314
DOIs	https://doi.org/10.1007/978-3-540-30499-9_157
Publication status	Published - 2004
Externally published	Yes
Event	11th International Conference on Neural Information Processing, ICONIP 2004 - Calcutta, India Duration: 22 Nov 2004 → 25 Nov 2004

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer Berlin, Heidelberg
Volume	3316)
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	11th International Conference on Neural Information Processing, ICONIP 2004
Country/Territory	India
City	Calcutta
Period	22/11/04 → 25/11/04

Access to Document

10.1007/978-3-540-30499-9_157

Cite this

TANG, E. K., SUGANTHAN, P. N., & YAO, X. (2004). Nonlinear feature extraction using evolutionary algorithm. In N. R. PAL, N. KASABOV, R. K. MUDI, S. PAL, & S. K. PARUI (Eds.), Neural Information Processing : 11th International Conference, ICONIP 2004 Calcutta, India, November 22–25, 2004 Proceedings (pp. 1014-1019). (Lecture Notes in Computer Science; Vol. 3316)). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-30499-9_157

TANG, E.K. ; SUGANTHAN, Ponnuthurai Nagaratnan ; YAO, Xin. / Nonlinear feature extraction using evolutionary algorithm. Neural Information Processing : 11th International Conference, ICONIP 2004 Calcutta, India, November 22–25, 2004 Proceedings. editor / Nikhil Ranjan PAL ; Nik KASABOV ; Rajani K. MUDI ; Srimanta PAL ; Swapan Kumar PARUI. Springer Berlin Heidelberg, 2004. pp. 1014-1019 (Lecture Notes in Computer Science).

@inproceedings{5587a277111e4abaaf5a9ee54e7f2ecb,

title = "Nonlinear feature extraction using evolutionary algorithm",

abstract = "We propose a method of nonlinear feature extraction for 2-class problems. A simple sigmoid function is used to extract features that are negatively correlated to each other. To evaluate the effectiveness of the proposed method, we employ linear and non-linear support vector machines to classify using the extracted feature sets and the original feature sets. Comparison on 4 datasets shows that our method is effective for nonlinear feature extraction. {\textcopyright} Springer-Verlag Berlin Heidelberg 2004.",

author = "E.K. TANG and SUGANTHAN, {Ponnuthurai Nagaratnan} and Xin YAO",

year = "2004",

doi = "10.1007/978-3-540-30499-9_157",

language = "English",

isbn = "9783540239314",

series = "Lecture Notes in Computer Science",

publisher = "Springer Berlin Heidelberg",

pages = "1014--1019",

editor = "PAL, {Nikhil Ranjan} and Nik KASABOV and MUDI, {Rajani K.} and Srimanta PAL and PARUI, {Swapan Kumar}",

booktitle = "Neural Information Processing : 11th International Conference, ICONIP 2004 Calcutta, India, November 22–25, 2004 Proceedings",

note = "11th International Conference on Neural Information Processing, ICONIP 2004 ; Conference date: 22-11-2004 Through 25-11-2004",

}

TANG, EK, SUGANTHAN, PN & YAO, X 2004, Nonlinear feature extraction using evolutionary algorithm. in NR PAL, N KASABOV, RK MUDI, S PAL & SK PARUI (eds), Neural Information Processing : 11th International Conference, ICONIP 2004 Calcutta, India, November 22–25, 2004 Proceedings. Lecture Notes in Computer Science, vol. 3316), Springer Berlin Heidelberg, pp. 1014-1019, 11th International Conference on Neural Information Processing, ICONIP 2004, Calcutta, India, 22/11/04. https://doi.org/10.1007/978-3-540-30499-9_157

Nonlinear feature extraction using evolutionary algorithm. / TANG, E.K.; SUGANTHAN, Ponnuthurai Nagaratnan; YAO, Xin.
Neural Information Processing : 11th International Conference, ICONIP 2004 Calcutta, India, November 22–25, 2004 Proceedings. ed. / Nikhil Ranjan PAL; Nik KASABOV; Rajani K. MUDI; Srimanta PAL; Swapan Kumar PARUI. Springer Berlin Heidelberg, 2004. p. 1014-1019 (Lecture Notes in Computer Science; Vol. 3316)).

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

TY - GEN

T1 - Nonlinear feature extraction using evolutionary algorithm

AU - TANG, E.K.

AU - SUGANTHAN, Ponnuthurai Nagaratnan

AU - YAO, Xin

PY - 2004

Y1 - 2004

N2 - We propose a method of nonlinear feature extraction for 2-class problems. A simple sigmoid function is used to extract features that are negatively correlated to each other. To evaluate the effectiveness of the proposed method, we employ linear and non-linear support vector machines to classify using the extracted feature sets and the original feature sets. Comparison on 4 datasets shows that our method is effective for nonlinear feature extraction. © Springer-Verlag Berlin Heidelberg 2004.

AB - We propose a method of nonlinear feature extraction for 2-class problems. A simple sigmoid function is used to extract features that are negatively correlated to each other. To evaluate the effectiveness of the proposed method, we employ linear and non-linear support vector machines to classify using the extracted feature sets and the original feature sets. Comparison on 4 datasets shows that our method is effective for nonlinear feature extraction. © Springer-Verlag Berlin Heidelberg 2004.

UR - http://www.scopus.com/inward/record.url?scp=32144453040&partnerID=8YFLogxK

U2 - 10.1007/978-3-540-30499-9_157

DO - 10.1007/978-3-540-30499-9_157

M3 - Conference paper (refereed)

SN - 9783540239314

T3 - Lecture Notes in Computer Science

SP - 1014

EP - 1019

BT - Neural Information Processing : 11th International Conference, ICONIP 2004 Calcutta, India, November 22–25, 2004 Proceedings

A2 - PAL, Nikhil Ranjan

A2 - KASABOV, Nik

A2 - MUDI, Rajani K.

A2 - PAL, Srimanta

A2 - PARUI, Swapan Kumar

PB - Springer Berlin Heidelberg

T2 - 11th International Conference on Neural Information Processing, ICONIP 2004

Y2 - 22 November 2004 through 25 November 2004

ER -

TANG EK, SUGANTHAN PN, YAO X. Nonlinear feature extraction using evolutionary algorithm. In PAL NR, KASABOV N, MUDI RK, PAL S, PARUI SK, editors, Neural Information Processing : 11th International Conference, ICONIP 2004 Calcutta, India, November 22–25, 2004 Proceedings. Springer Berlin Heidelberg. 2004. p. 1014-1019. (Lecture Notes in Computer Science). doi: 10.1007/978-3-540-30499-9_157

Nonlinear feature extraction using evolutionary algorithm

Abstract

Publication series

Conference

Access to Document

Other files and links

Fingerprint

Cite this