Journal
NEUROCOMPUTING
Volume 55, Issue 1-2, Pages 169-186Publisher
ELSEVIER
DOI: 10.1016/S0925-2312(03)00431-4
Keywords
benchmark; comparative study; support vector machines; regression; classification
Categories
Ask authors/readers for more resources
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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available