Sparse Kernel Modelling: A Unified Approach
Chen, S., Hong, X. and Harris, C.J. (2007) Sparse Kernel Modelling: A Unified Approach. At 8th International Conference on Intelligent Data Engineering and Automated Learning, Birmingham, UK, 16 - 19 Dec 2007. , 27-36.
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Description/Abstract
A unified approach is proposed for sparse kernel data modelling that includes regression and classification as well as probability density function estimation. The orthogonal-least-squares forward selection method based on the leave-one-out test criteria is presented within this unified data-modelling framework to construct sparse kernel models that generalise well. Examples from regression, classification and density estimation applications are used to illustrate the effectiveness of this generic sparse kernel data modelling approach.
| Item Type: | Conference or Workshop Item (Speech) |
|---|---|
| Additional Information: | Event Dates: December 16-19, 2007 |
| ISSNs: | 0302-9743 |
| Divisions: | Faculty of Physical and Applied Science > Electronics and Computer Science > Comms, Signal Processing & Control |
| Item ID: | 264986 |
| Date Deposited: | 20 Dec 2007 11:16 |
| Last Modified: | 21 Aug 2012 04:18 |
| Contributors: | Chen, S. (Author) Hong, X. (Author) Harris, C.J. (Author) |
| Date: | December 2007 |
| Additional Information: | Event Dates: December 16-19, 2007 |
| Status: | Published |
| Further Information: | Google Scholar |
| ISI Citation Count: | 0 |
| URI: | http://eprints.soton.ac.uk/id/eprint/264986 |
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