Thu, 24 Jul 2008 23:15:00 BST CiteULike: AbnerCYH's Hornik http://www.citeulike.org/user/AbnerCYH/author/Hornik CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/user/AbnerCYH/article/2776513 <i>Neurocomputing, Vol. 55, No. 1-2. (September 2003), pp. 169-186.</i><br /><br />Support vector machines (SVMs) are rarely benchmarked against other classification or regression methods. We compare a popular SVM implementation (libsvm) to 16 classification methods and 9 regression methods--all accessible through the software --by the means of standard performance measures (classification error and mean squared error) which are also analyzed by the means of bias-variance decompositions. SVMs showed mostly good performances both on classification and regression tasks, but other methods proved to be very competitive. The support vector machine under test David Meyer Friedrich Leisch Kurt Hornik doi:10.1016/S0925-2312(03)00431-4 Neurocomputing, Vol. 55, No. 1-2. (September 2003), pp. 169-186. 2008-05-09T19:40:26-00:00 2003 Neurocomputing 55 1-2 169 186 algebra algorithms kdd optimization stochastic