An excellent feature selection model using gradient-based and point injection techniques

D. Huang; Tommy W. S. Chow

doi:10.1007/11893257_76

An excellent feature selection model using gradient-based and point injection techniques

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

Abstract

This paper focuses on enhancing the effectiveness of filter feature selection models from two aspects. One is to modify feature searching engines based on optimization theory, and the other is to improve the regularization capability using point injection techniques. The second topic is undoubtedly important in the situations where overfitting is likely to be met, for example, the ones with only small sample sets available. Synthetic and real data are used to demonstrate the contribution of our proposed strategies. © Springer-Verlag Berlin Heidelberg 2006.

Original language	English
Title of host publication	Neural Information Processing
Subtitle of host publication	13th International Conference, ICONIP 2006, Hong Kong, China, October 3-6, 2006, Proceedings, Part II
Editors	Irwin King, Jun Wang, Lai-Wan Chan
Publisher	Springer
Pages	679-692
ISBN (Electronic)	978-3-540-46482-2
ISBN (Print)	9783540464815
DOIs	https://doi.org/10.1007/11893257_76
Publication status	Published - 2006
Event	13th International Conference on Neural Information Processing (ICONIP 2006) - Hong Kong, China Duration: 3 Oct 2006 → 6 Oct 2006

Publication series

Name	Lecture Notes in Computer Science
Volume	4233
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	13th International Conference on Neural Information Processing (ICONIP 2006)
Place	China
City	Hong Kong
Period	3/10/06 → 6/10/06

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Huang, D., & Chow, T. W. S. (2006). An excellent feature selection model using gradient-based and point injection techniques. In I. King, J. Wang, & L.-W. Chan (Eds.), Neural Information Processing: 13th International Conference, ICONIP 2006, Hong Kong, China, October 3-6, 2006, Proceedings, Part II (pp. 679-692). (Lecture Notes in Computer Science; Vol. 4233). Springer . https://doi.org/10.1007/11893257_76

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title = "An excellent feature selection model using gradient-based and point injection techniques",

abstract = "This paper focuses on enhancing the effectiveness of filter feature selection models from two aspects. One is to modify feature searching engines based on optimization theory, and the other is to improve the regularization capability using point injection techniques. The second topic is undoubtedly important in the situations where overfitting is likely to be met, for example, the ones with only small sample sets available. Synthetic and real data are used to demonstrate the contribution of our proposed strategies. {\textcopyright} Springer-Verlag Berlin Heidelberg 2006.",

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

year = "2006",

doi = "10.1007/11893257_76",

language = "English",

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series = "Lecture Notes in Computer Science",

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pages = "679--692",

editor = "King, {Irwin } and Wang, {Jun } and Chan, {Lai-Wan }",

booktitle = "Neural Information Processing",

note = "13th International Conference on Neural Information Processing (ICONIP 2006) ; Conference date: 03-10-2006 Through 06-10-2006",

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Huang, D & Chow, TWS 2006, An excellent feature selection model using gradient-based and point injection techniques. in I King, J Wang & L-W Chan (eds), Neural Information Processing: 13th International Conference, ICONIP 2006, Hong Kong, China, October 3-6, 2006, Proceedings, Part II. Lecture Notes in Computer Science, vol. 4233, Springer , pp. 679-692, 13th International Conference on Neural Information Processing (ICONIP 2006), Hong Kong, China, 3/10/06. https://doi.org/10.1007/11893257_76

An excellent feature selection model using gradient-based and point injection techniques. / Huang, D.; Chow, Tommy W. S.
Neural Information Processing: 13th International Conference, ICONIP 2006, Hong Kong, China, October 3-6, 2006, Proceedings, Part II. ed. / Irwin King; Jun Wang; Lai-Wan Chan. Springer , 2006. p. 679-692 (Lecture Notes in Computer Science; Vol. 4233).

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

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AU - Chow, Tommy W. S.

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N2 - This paper focuses on enhancing the effectiveness of filter feature selection models from two aspects. One is to modify feature searching engines based on optimization theory, and the other is to improve the regularization capability using point injection techniques. The second topic is undoubtedly important in the situations where overfitting is likely to be met, for example, the ones with only small sample sets available. Synthetic and real data are used to demonstrate the contribution of our proposed strategies. © Springer-Verlag Berlin Heidelberg 2006.

AB - This paper focuses on enhancing the effectiveness of filter feature selection models from two aspects. One is to modify feature searching engines based on optimization theory, and the other is to improve the regularization capability using point injection techniques. The second topic is undoubtedly important in the situations where overfitting is likely to be met, for example, the ones with only small sample sets available. Synthetic and real data are used to demonstrate the contribution of our proposed strategies. © Springer-Verlag Berlin Heidelberg 2006.

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Huang D, Chow TWS. An excellent feature selection model using gradient-based and point injection techniques. In King I, Wang J, Chan LW, editors, Neural Information Processing: 13th International Conference, ICONIP 2006, Hong Kong, China, October 3-6, 2006, Proceedings, Part II. Springer . 2006. p. 679-692. (Lecture Notes in Computer Science). Epub 2006 Oct 3. doi: 10.1007/11893257_76

An excellent feature selection model using gradient-based and point injection techniques

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