Hi Achim,
Thank you so much for your reply, could you please tell me how i call PLS . i' m sorry i tried but could not. Many thanks Amy > Date: Thu, 4 Feb 2010 02:31:36 +0100 > From: achim.zeil...@wu-wien.ac.at > To: amy_4_5...@hotmail.com > CC: mailinglist.honey...@gmail.com; r-help@r-project.org > Subject: Re: [R] svm > > On Thu, 4 Feb 2010, Amy Hessen wrote: > > > > > > > Hi Steve, > > > > > > > > Thank you very much for your reply. > > > > Could you please guide me to any helpful reference to learn about the > > other non-linear regression algorithms available in R language and about > > how I use any of them? > > There are a few papers in the Journal of Statistical Software that might > be interesting for you. The paper about the "caret" package gives a good > overview, many further pointers, and an easy-to-use interface (see > http://www.jstatsoft.org/v28/i05/). There is also a comparison of Support > Vector Machines in R (in http://www.jstatsoft.org/v15/i09/). Further > interesting issues might be kernlab (http://www.jstatsoft.org/v11/i09/) or > glmnet (http://www.jstatsoft.org/v33/i01/) among others. > > See also the Machine Learning task view > > http://CRAN.R-project.org/view=MachineLearning > > for other approaches and their implementations. > > hth, > Z > > > Cheers,Amyate: Wed, 3 Feb 2010 10:59:27 -0500 > >> Subject: Re: [R] svm > >> From: mailinglist.honey...@gmail.com > >> To: amy_4_5...@hotmail.com > >> CC: r-help@r-project.org > >> > >> HI Amy, > >> > >> On Wed, Feb 3, 2010 at 1:56 AM, Amy Hessen <amy_4_5...@hotmail.com> wrote: > >>> > >>> Hi Steve, > >>> > >>> Could you please help me in this point?: > >>> > >>> I use SVM of R and I?m trying some datasets from UCI but when I compare > >>> the > >>> results of my program( that does not do anything more than calling SVM) > >>> with > >>> the RMSE of SVM in any other paper, I found a big gap between them. > >>> > >>> For example, this is the rmse of svm of my program for the dataset > >>> bodyfat: > >>> 2.64561 > >>> > >>> And this is the RMSE of a paper 0.0204. > >>> > >>> Could you please tell me how I can reduce this gap in the performance of > >>> SVM? > >> > >> Sorry, it's hard to say w/o investing any real time to investigate > >> (and I unfortunately don't have the time to do so). > >> > >> There are different parameters you can play with in nu-regression vs. > >> eps-regression and different kernel functions that can be used that > >> might be a better fit for the type of data you are trying to learn > >> against. > >> > >> Before running the SVM (or any other "learning" alogorithm), there are > >> also ways to normalize your data, too .. > >> > >> Lots of things to look at ... > >> > >> -steve > >> > >> -- > >> Steve Lianoglou > >> Graduate Student: Computational Systems Biology > >> | Memorial Sloan-Kettering Cancer Center > >> | Weill Medical College of Cornell University > >> Contact Info: http://cbio.mskcc.org/~lianos/contact > > > > _________________________________________________________________ > > [[elided Hotmail spam]] > > > > [[alternative HTML version deleted]] > > > > _________________________________________________________________ messenger [[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.
