Chew, H.Lim, C.2009-09-182009-09-182009Journal of Industrial and Management Optimization, 2009; 5(2):403-4151547-58161553-166Xhttp://hdl.handle.net/2440/50932The 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.enSupport Vector MachinePattern recognitionQuadratic optimisation.Journal article002009053110.3934/jimo.2009.5.4030002651908000162-s2.0-6764949472239014Chew, H. [0000-0001-6525-574X]Lim, C. [0000-0002-2463-9760]