Unbiased linear neural-based fusion with normalized weighted average algorithm for regression

Yunfeng Wu; S. C. Ng

doi:10.1007/978-3-540-72393-6_79

Unbiased linear neural-based fusion with normalized weighted average algorithm for regression

Yunfeng Wu, S. C. Ng

Hong Kong Metropolitan University

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

6 Citations (Scopus)

Abstract

Regression is a very important data mining problem. In this paper, we present a new unbiased linear fusion method that combines component predictors so as to solve regression problems. The fusion weighted coefficients assigned are normalized, and updated by estimating the prediction errors between the component predictors and the desired regression values. The empirical results of our regression experiments on five synthetic and four benchmark data sets show that the proposed fusion method improves prediction accuracy in terms of mean-squared error, and also provides the regression curves with better fidelity with respect to normalized correlation coefficients, compared with the popular simple average and weighted average fusion rules.

Original language	English
Title of host publication	Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings
Pages	664-670
Number of pages	7
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-540-72393-6_79
Publication status	Published - 2007
Event	4th International Symposium on Neural Networks, ISNN 2007 - Nanjing, China Duration: 3 Jun 2007 → 7 Jun 2007

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	4492 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	4th International Symposium on Neural Networks, ISNN 2007
Country/Territory	China
City	Nanjing
Period	3/06/07 → 7/06/07

Access to Document

10.1007/978-3-540-72393-6_79

Cite this

Wu, Y., & Ng, S. C. (2007). Unbiased linear neural-based fusion with normalized weighted average algorithm for regression. In Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings (PART 2 ed., pp. 664-670). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4492 LNCS, No. PART 2). https://doi.org/10.1007/978-3-540-72393-6_79

Wu, Yunfeng ; Ng, S. C. / Unbiased linear neural-based fusion with normalized weighted average algorithm for regression. Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 2. ed. 2007. pp. 664-670 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

@inproceedings{b1504d4019a0412d97794e8456c8806c,

title = "Unbiased linear neural-based fusion with normalized weighted average algorithm for regression",

abstract = "Regression is a very important data mining problem. In this paper, we present a new unbiased linear fusion method that combines component predictors so as to solve regression problems. The fusion weighted coefficients assigned are normalized, and updated by estimating the prediction errors between the component predictors and the desired regression values. The empirical results of our regression experiments on five synthetic and four benchmark data sets show that the proposed fusion method improves prediction accuracy in terms of mean-squared error, and also provides the regression curves with better fidelity with respect to normalized correlation coefficients, compared with the popular simple average and weighted average fusion rules.",

author = "Yunfeng Wu and Ng, {S. C.}",

year = "2007",

doi = "10.1007/978-3-540-72393-6_79",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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booktitle = "Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings",

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Wu, Y & Ng, SC 2007, Unbiased linear neural-based fusion with normalized weighted average algorithm for regression. in Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 4492 LNCS, pp. 664-670, 4th International Symposium on Neural Networks, ISNN 2007, Nanjing, China, 3/06/07. https://doi.org/10.1007/978-3-540-72393-6_79

Unbiased linear neural-based fusion with normalized weighted average algorithm for regression. / Wu, Yunfeng; Ng, S. C.
Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 2. ed. 2007. p. 664-670 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4492 LNCS, No. PART 2).

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

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AB - Regression is a very important data mining problem. In this paper, we present a new unbiased linear fusion method that combines component predictors so as to solve regression problems. The fusion weighted coefficients assigned are normalized, and updated by estimating the prediction errors between the component predictors and the desired regression values. The empirical results of our regression experiments on five synthetic and four benchmark data sets show that the proposed fusion method improves prediction accuracy in terms of mean-squared error, and also provides the regression curves with better fidelity with respect to normalized correlation coefficients, compared with the popular simple average and weighted average fusion rules.

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DO - 10.1007/978-3-540-72393-6_79

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Wu Y, Ng SC. Unbiased linear neural-based fusion with normalized weighted average algorithm for regression. In Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 2 ed. 2007. p. 664-670. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-540-72393-6_79

Unbiased linear neural-based fusion with normalized weighted average algorithm for regression

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