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https://hdl.handle.net/2440/50932
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Type: | Journal article |
Title: | On regularisation parameter transformation of support vector machines |
Author: | Chew, H. Lim, C. |
Citation: | Journal of Industrial and Management Optimization, 2009; 5(2):403-415 |
Publisher: | American Institute of Mathematical Sciences |
Issue Date: | 2009 |
ISSN: | 1547-5816 1553-166X |
Statement of Responsibility: | Hong-Gunn Chew and Cheng-Chew Lim |
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. |
Keywords: | Support Vector Machine Pattern recognition Quadratic optimisation. |
DOI: | 10.3934/jimo.2009.5.403 |
Published version: | http://dx.doi.org/10.3934/jimo.2009.5.403 |
Appears in Collections: | Aurora harvest 5 Electrical and Electronic Engineering publications |
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