Orthogonal Least Square with Boosting for Regression
Chen, S., Wang, X.X. and Brown, D.J. (2004) Orthogonal Least Square with Boosting for Regression. In, 5th International Conference on Data Engineering and Automated Learning, Exeter, UK, 25 - 27 Aug 2004. Springer, 593-599.
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Description/Abstract
A novel technique is presented to construct sparse regression models based on the orthogonal least square method with boosting. This technique tunes the mean vector and diagonal covariance matrix of individual regressor by incrementally minimizing the training mean square error. A weighted optimization method is developed based on boosting to append regressors one by one in an orthogonal forward selection procedure. Experimental results obtained using this technique demonstrate that it offers a viable alternative to the existing state-of-art kernel modeling methods for constructing parsimonious regression models.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Additional Information: | Springer LNCS 3177 The paper received the best paper award. Event Dates: August 25-27, 2004 |
| ISBNs: | 3540228810 |
| ISSNs: | 0302-9743 |
| Divisions: | Faculty of Physical and Applied Science > Electronics and Computer Science > Comms, Signal Processing & Control |
| Item ID: | 259859 |
| Date Deposited: | 30 Aug 2004 |
| Last Modified: | 18 Aug 2012 03:38 |
| Contributors: | Chen, S. (Author) Wang, X.X. (Author) Brown, D.J. (Author) Yang, Z.R. (Editor) Everson, R. (Editor) Yin, H.J. (Editor) |
| Date: | 2004 |
| Additional Information: | Springer LNCS 3177 The paper received the best paper award. Event Dates: August 25-27, 2004 |
| Status: | Published |
| Publisher: | Springer |
| Further Information: | Google Scholar |
| ISI Citation Count: | 0 |
| URI: | http://eprints.soton.ac.uk/id/eprint/259859 |
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