| Vol. 25 | Vol. 24* | Vol. 23 | Vol. 22* |
| Vol. 21 | Vol. 20* | Vol. 19 | Vol. 18* |
| Vol. 17 | Vol. 16 | Vol. 15 | Vol. 14 |
| Vol. 13* | Vol. 12 | Vol. 11 | Vol. 10* |
| Vol. 9 | Vol. 8 | Vol. 7 | Vol. 6 |
| Vol. 5 | Vol. 4 | Vol. 3 | Vol. 2 |
| Vol. 1 | |||
| * = Special Volume | |||
| Authors: | Alexandros Karatzoglou, David Meyer, Kurt Hornik |
| Title: | [download] (3357)Support Vector Machines in R |
| Reference: | Vol. 15, Issue 9, Apr 2006 Submitted 2005-10-24, Accepted 2006-04-06 |
| Type: | Article |
| Abstract: | Being among the most popular and efficient classification and regression methods currently available, implementations of support vector machines exist in almost every popular programming language. Currently four R packages contain SVM related software. The purpose of this paper is to present and compare these implementations. |
| Paper: | [download] (3357)Support Vector Machines in R (application/pdf, 1.2 MB) |
| Resources: | BibTeX | OAI |