Support Vector Machines in R

Support Vector Machines in R

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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 com...

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Main Authors: Alexandros Karatzoglou, David Meyer, Kurt Hornik
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2006-04-01
Series:Journal of Statistical Software
Online Access:http://www.jstatsoft.org/index.php/jss/article/view/1484
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spelling doaj-ff2d1fa7a1a14a17be9230aa72bae2462020-11-24T22:13:40ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602006-04-0115112810.18637/jss.v015.i0988Support Vector Machines in RAlexandros KaratzoglouDavid MeyerKurt HornikBeing 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.http://www.jstatsoft.org/index.php/jss/article/view/1484
collection DOAJ
language English
format Article
sources DOAJ
author Alexandros Karatzoglou
David Meyer
Kurt Hornik
spellingShingle Alexandros Karatzoglou
David Meyer
Kurt Hornik
Support Vector Machines in R
Journal of Statistical Software
author_facet Alexandros Karatzoglou
David Meyer
Kurt Hornik
author_sort Alexandros Karatzoglou
title Support Vector Machines in R
title_short Support Vector Machines in R
title_full Support Vector Machines in R
title_fullStr Support Vector Machines in R
title_full_unstemmed Support Vector Machines in R
title_sort support vector machines in r
publisher Foundation for Open Access Statistics
series Journal of Statistical Software
issn 1548-7660
publishDate 2006-04-01
description 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.
url http://www.jstatsoft.org/index.php/jss/article/view/1484
work_keys_str_mv AT alexandroskaratzoglou supportvectormachinesinr
AT davidmeyer supportvectormachinesinr
AT kurthornik supportvectormachinesinr
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