Name
Abstract | ||
|---|---|---|
We study the relation between support vector machines (SVMs) for regression (SVMR) and SVM for classification (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 $\epsilon$ sufficiently close to one, the optimal hyperplane and threshold for the SVMC problem with regularization parameter C_c are equal to (1-\epsilon)^{- 1} times the optimal hyperplane and threshold for SVMR with regularization parameter C_r = (1-\epsilon)C_c. A direct consequence of this result is that SVMC can be seen as a special case of SVMR. |
Year | Venue | Keywords |
|---|---|---|
1999 | ESANN | support vector machines,support vector machine,certain choice,special case,regularization parameter c_c,svmc problem,optimal hyperplane,direct consequence,regularization parameter,svmr solution,svmc solution |
DocType | Citations | PageRank |
Conference | 3 | 7.60 |
References | Authors | |
1 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Massimiliano Pontil | 1 | 5820 | 472.96 |
| Ryan Rifkin | 2 | 709 | 49.57 |
| Theodoros Evgeniou | 3 | 3005 | 219.65 |