Support vector machines in R

Alexandros Karatzoglou; David Meyer; Kurt Hornik

Support vector machines in R

Alexandros Karatzoglou
, David Meyer
, Kurt Hornik

Publikation: Wissenschaftliche Fachzeitschrift › Originalbeitrag in Fachzeitschrift › Begutachtung

494 Downloads (Pure)

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)

Originalsprache	Englisch
Seiten (von - bis)	1 - 28
Fachzeitschrift	Journal of Statistical Software
Volume	15
Ausgabenummer	9
Publikationsstatus	Veröffentlicht - 1 Okt. 2006

Bibliographische Notiz

Aktualisierte Version

Zugriff auf Dokument

SupportvectorEndgültige, publizierte Fassung, 1,22 MBLizenz: Sonstige

Andere Dateien und Links

http://www.jstatsoft.org/v15/i09/paper

1 WU Working Paper und Case

Support Vector Machines in R
Karatzoglou, A., Meyer, D. & Hornik, K., 2005, October 2005 Aufl., Vienna: Department of Statistics and Mathematics, WU Vienna University of Economics and Business, (Research Report Series / Department of Statistics and Mathematics; Nr. 21).
Publikation: Working/Discussion Paper › WU Working Paper und Case

Open Access
Datei

578 Downloads (Pure)

Zitat

@article{2cac54acc8934576a792e1ee0f981d83,

title = "Support vector machines in R",

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)",

author = "Alexandros Karatzoglou and David Meyer and Kurt Hornik",

note = "Updated version",

year = "2006",

month = oct,

day = "1",

language = "English",

volume = "15",

pages = "1 -- 28",

journal = "Journal of Statistical Software",

issn = "1548-7660",

publisher = "University of California at Los Angeles",

number = "9",

}

TY - JOUR

T1 - Support vector machines in R

AU - Karatzoglou, Alexandros

AU - Meyer, David

AU - Hornik, Kurt

N1 - Updated version

PY - 2006/10/1

Y1 - 2006/10/1

N2 - 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)

AB - 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)

UR - http://www.jstatsoft.org/v15/i09/paper

M3 - Journal article

SN - 1548-7660

VL - 15

SP - 1

EP - 28

JO - Journal of Statistical Software

JF - Journal of Statistical Software

IS - 9

ER -

Support vector machines in R

Abstract

Bibliographische Notiz

Zugriff auf Dokument

Andere Dateien und Links

Publikationen

Support Vector Machines in R

Zitat