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
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