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book about "support vector machines"

7 messages · manuel.martin, Neeti, Georg Ruß +4 more

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On 03/12/10 16:23:33, manuel.martin wrote:
Hi Manuel,

there's also the references mentioned in ?svm once you've loaded the e1071
library. Nevertheless, that's rather detailed on the implementation side,
not on the general picture that I assume you'd like for a book.

library("e1071")
?svm

There's also the downloadable "A guide for beginners: C.-W. Hsu, C.-C.
Chang, C.-J.  Lin. A practical guide to support vector classification"
mentioned in the "additional information" section of
http://www.csie.ntu.edu.tw/~cjlin/libsvm/ (which, in turn, is from ?svm)

Regards,
Georg.
--
Research Assistant
Otto-von-Guericke-Universit?t Magdeburg
research at georgruss.de
http://research.georgruss.de
2 days later
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My favorite book on SVM is Learning with Kernels by Scholkopf and Smola. You might also want to consider a relevance vector machine, which is a more recent development. RVM is Bayesian-based and usually produces a sparser representation than a SVM. Check out Mike Tipping's web site at
http://www.miketipping.com/

There is also a good description of RVM in Bishop's book: Pattern Recognition and Machine Learning.

David Reinke

Senior Transportation Engineer/Economist
Dowling Associates, Inc.
180 Grand Avenue, Suite 250
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-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of km
Sent: Friday, December 03, 2010 10:16 PM
To: Georg Ru?
Cc: r-help at r-project.org; manuel.martin
Subject: Re: [R] book about "support vector machines"

a bit of caution.
the latest version of libsvm is not yet available in the  e1071 R-package.

regards,
KM
On Fri, Dec 3, 2010 at 9:52 PM, Georg Ru_ <research at georgruss.de> wrote:

            

  
  
#
Hi,

On Fri, Dec 3, 2010 at 10:23 AM, manuel.martin
<manuel.martin at orleans.inra.fr> wrote:
Here's another intro to support vector regression:
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.99.2073&rep=rep1&type=pdf