From Regression to Classication in Support Vector Machines
We study the relation between support vector machines (SVMs) for regression (SVMR) and SVM for classication (SVMC). We show that for a given SVMC solution there exists a SVMR solution which is equivalent for a certain choice of the parameters. In particular our result is that for suciently close to one, the optimal hyperplane and threshold for the SVMC problem with regularization parameter Cc are equal to 1 1 times the optimal hyperplane and threshold for SVMR with regularization parameter Cr =( 1 )Cc. A direct consequence of this result is that SVMC can be seen as a special case of SVMR.