[R] Looking for packages to do Feature Selection and Classification

[Weiwei Shi]

FYI:

check the following paper on svm (using libsvm) as well as random
forest in the context of feature selection.

http://www.csie.ntu.edu.tw/~cjlin/papers/features.pdf

HTH

On 1/4/06, Diaz.Ramon <rdiaz at cnio.es> wrote:
> Dear Frank,
> I expect you'll get many different answers since a wide variety of approaches have been suggested. So I'll stick to self-advertisment: I've written an R package, varSelRF (available from R), that uses random forest together with a simple variable selection approach, and provides also bootstrap estimates of the error rate of the procedure. Andy Liaw and collaborators previously developed and published a somewhat similar procedure. You probably also want to take a look at several packages available from BioConductor.
>
> Best,
>
> R.
>
>
> -----Original Message-----
> From:   r-help-bounces at stat.math.ethz.ch on behalf of Frank Duan
> Sent:   Wed 1/4/2006 4:23 AM
> To:     r-help
> Cc:
> Subject:        [R] Looking for packages to do Feature Selection and Classification
>
> Hi All,
>
> Sorry if this is a repost (a quick browse didn't give me the answer).
>
> I wonder if there are packages that can do the feature selection and
> classification at the same time. For instance, I am using SVM to classify my
> samples, but it's easy to get overfitted if using all of the features. Thus,
> it is necessary to select "good" features to build an optimum hyperplane
> (?). Here is a simple example: Suppose I have 100 "useful" features and 100
> "useless" features (or noise features), I want the SVM to give me the
> same results when 1) using only 100 useful features or 2) using all 200
> features.
>
> Any suggestions or point me to a reference?
>
> Thanks in advance!
>
> Frank
>
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--
Weiwei Shi, Ph.D

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