Karatzoglou, Alexandros and Meyer, David and Hornik, Kurt ORCID: https://orcid.org/0000-0003-4198-9911
(2006)
Support Vector Machines in R.
Journal of Statistical Software, 15 (9).
pp. 1-28.
ISSN 1548-7660
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Official URL: http://www.jstatsoft.org/v15/i09/paper
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. (authors' abstract)
Item Type: | Article |
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Keywords: | support vector machines / R |
Divisions: | Departments > Finance, Accounting and Statistics > Statistics and Mathematics > Hornik |
Version of the Document: | Published |
Depositing User: | ePub Administrator |
Date Deposited: | 09 Oct 2013 12:38 |
Last Modified: | 28 Oct 2019 09:09 |
FIDES Link: | https://bach.wu.ac.at/d/research/results/34465/ |
URI: | https://epub.wu.ac.at/id/eprint/3986 |
Available Versions of this Item
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Support Vector Machines in R. (deposited 24 Oct 2005 15:15)
- Support Vector Machines in R. (deposited 09 Oct 2013 12:38) [Currently Displayed]
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