Searching optimal feature subset using mutual information

D. Huang; Tommy W.S. Chow

Searching optimal feature subset using mutual information

D. Huang
, Tommy W.S. Chow

Department of Electrical Engineering

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

4 Citations (Scopus)

Abstract

A novel feature selection methodology is proposed with the concept of mutual information. The proposed methodology effectively circumvents two major problems in feature selection process: to identify the irrelevancy and redundancy in the feature set, and to estimate the optimal feature subset for classification task. © ESANN 2003. All Rights Reserved.

Original language	English
Title of host publication	ESANN 2003 Proceedings - 11th European Symposium on Artificial Neural Networks
Publisher	d-side publication
Pages	161-166
Publication status	Published - 2003
Event	11th European Symposium on Artificial Neural Networks, ESANN 2003 - Bruges, Belgium Duration: 23 Apr 2003 → 25 Apr 2003 https://www.esann.org/proceedings/2003

Publication series

Name	ESANN 2003 Proceedings - 11th European Symposium on Artificial Neural Networks

Conference

Conference	11th European Symposium on Artificial Neural Networks, ESANN 2003
Place	Belgium
City	Bruges
Period	23/04/03 → 25/04/03
Internet address	https://www.esann.org/proceedings/2003

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

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title = "Searching optimal feature subset using mutual information",

abstract = "A novel feature selection methodology is proposed with the concept of mutual information. The proposed methodology effectively circumvents two major problems in feature selection process: to identify the irrelevancy and redundancy in the feature set, and to estimate the optimal feature subset for classification task. {\textcopyright} ESANN 2003. All Rights Reserved.",

author = "D. Huang and Chow, \{Tommy W.S.\}",

note = "Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].; 11th European Symposium on Artificial Neural Networks, ESANN 2003 ; Conference date: 23-04-2003 Through 25-04-2003",

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language = "English",

series = "ESANN 2003 Proceedings - 11th European Symposium on Artificial Neural Networks",

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pages = "161--166",

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Huang, D & Chow, TWS 2003, Searching optimal feature subset using mutual information. in ESANN 2003 Proceedings - 11th European Symposium on Artificial Neural Networks. ESANN 2003 Proceedings - 11th European Symposium on Artificial Neural Networks, d-side publication, pp. 161-166, 11th European Symposium on Artificial Neural Networks, ESANN 2003, Bruges, Belgium, 23/04/03.

Searching optimal feature subset using mutual information. / Huang, D.; Chow, Tommy W.S.
ESANN 2003 Proceedings - 11th European Symposium on Artificial Neural Networks. d-side publication, 2003. p. 161-166 (ESANN 2003 Proceedings - 11th European Symposium on Artificial Neural Networks).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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AB - A novel feature selection methodology is proposed with the concept of mutual information. The proposed methodology effectively circumvents two major problems in feature selection process: to identify the irrelevancy and redundancy in the feature set, and to estimate the optimal feature subset for classification task. © ESANN 2003. All Rights Reserved.

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M3 - RGC 32 - Refereed conference paper (with host publication)

T3 - ESANN 2003 Proceedings - 11th European Symposium on Artificial Neural Networks

SP - 161

EP - 166

BT - ESANN 2003 Proceedings - 11th European Symposium on Artificial Neural Networks

PB - d-side publication

T2 - 11th European Symposium on Artificial Neural Networks, ESANN 2003

Y2 - 23 April 2003 through 25 April 2003

ER -

Searching optimal feature subset using mutual information

Abstract

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