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.