On regularisation parameter transformation of support vector machines
| dc.contributor.author | Chew, H. | |
| dc.contributor.author | Lim, C. | |
| dc.date.issued | 2009 | |
| dc.description.abstract | The Dual-nu Support Vector Machine (SVM) is an effective method in pattern recognition and target detection. It improves on the Dual-C SVM, and offers competitive performance in detection and computation with traditional classifiers. We show that the regularisation parameters Dual-nu and Dual-C can be set such that the same SVM solution is obtained. We present the process of determining the related parameters of one form from the solution of a trained SVM of the other form, and test the relationship with a digit recognition problem. The link between the Dual-nu and Dual-C parameters allows users to use Dual-nu for ease of training, and to switch between the two forms readily. | |
| dc.description.statementofresponsibility | Hong-Gunn Chew and Cheng-Chew Lim | |
| dc.identifier.citation | Journal of Industrial and Management Optimization, 2009; 5(2):403-415 | |
| dc.identifier.doi | 10.3934/jimo.2009.5.403 | |
| dc.identifier.issn | 1547-5816 | |
| dc.identifier.issn | 1553-166X | |
| dc.identifier.orcid | Chew, H. [0000-0001-6525-574X] | |
| dc.identifier.orcid | Lim, C. [0000-0002-2463-9760] | |
| dc.identifier.uri | http://hdl.handle.net/2440/50932 | |
| dc.language.iso | en | |
| dc.publisher | American Institute of Mathematical Sciences | |
| dc.source.uri | https://doi.org/10.3934/jimo.2009.5.403 | |
| dc.subject | Support Vector Machine | |
| dc.subject | Pattern recognition | |
| dc.subject | Quadratic optimisation. | |
| dc.title | On regularisation parameter transformation of support vector machines | |
| dc.type | Journal article | |
| pubs.publication-status | Published |