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 Oakland, California 94612-3774 510.839.1742 x104 (voice) 510.839.0871 (fax) www.dowlinginc.com Please consider the environment before printing this e-mail. Confidentiality Notice: This e-mail message, including any attachments, is for the sole use of the intended recipient(s), and may contain confidential and privileged information. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply e-mail and destroy all copies of the original message. -----Original Message----- From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On Behalf Of km Sent: Friday, December 03, 2010 10:16 PM To: Georg Ruß Cc: r-help@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_ <resea...@georgruss.de> wrote: > On 03/12/10 16:23:33, manuel.martin wrote: > > I am currently looking for a book about support vector machines for > > regression and classification and am a bit lost since they are > > plenty of books dealing with this subject. I am not totally new to > > the field and would like to get more information on that subject for > > later use with the e1071 > > <http://cran.r-project.org/web/packages/e1071/index.html> > > package for instance. > > 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/<http://www.csie.ntu.edu.tw/% > 7Ecjlin/libsvm/>(which, in turn, is from ?svm) > > Regards, > Georg. > -- > Research Assistant > Otto-von-Guericke-Universitdt Magdeburg resea...@georgruss.de > http://research.georgruss.de > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
