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Wed Feb 3 16:59:27 CET 2010
On Wed, Feb 3, 2010 at 1:56 AM, Amy Hessen <amy_4_5_84 at 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:
> 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
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
Before running the SVM (or any other "learning" alogorithm), there are
also ways to normalize your data, too ..
Lots of things to look at ...
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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