期刊
NEUROCOMPUTING
卷 55, 期 1-2, 页码 169-186出版社
ELSEVIER
DOI: 10.1016/S0925-2312(03)00431-4
关键词
benchmark; comparative study; support vector machines; regression; classification
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 R-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. (C) 2003 Elsevier B.V. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据