R help - Mar 2012 - How to use a saved SVM model from e1071

Hello,

I have an SVM model previously calibrated using libsvm R implementation from
the e1071 package. 
I would like to use this SVM to predict values, from a Java program.
I first tried to use jlibsvm and the "standard" java implementation of
libsvm, without success.
Thus, I am now considering writing data in files from my Java code, calling
an R program to predict values, then gather the predicted values in Java.

The problem is that I do not know how to re-use the model saved using the
write.svm() function, since there is no read.svm() function.
I read the following message in the mailing archive, stating that I may use
the save and load methods built in R :
http://www.mail-archive.com/r-help at r-project.org/msg64428.html

Still, I am not sure how to pre-process the data and to post-process the
results.
Since write.svm() writes .scale and .ysale files as well as an svm file, I
figure that the scaling data is included in the svm object.

Does that mean that I do not have to worry about scaling my data and
unscaling the results provided by the predict function on a model reloaded
using save/load ?
I am asking this because I previously succeeded in loading the svm model
from libsvm in Java, but the results using unscaled data were obviously
wrong.

Thanks in advance,
Thomas

Hi Thomas,

On Wed, Mar 14, 2012 at 11:00 AM, Thomas Coffin
<thomas.coffin at artelys.com> wrote:
> Hello,
>
> I have an SVM model previously calibrated using libsvm R implementation
from
> the e1071 package.
> I would like to use this SVM to predict values, from a Java program.
> I first tried to use jlibsvm and the "standard" java
implementation of
> libsvm, without success.
> Thus, I am now considering writing data in files from my Java code, calling
> an R program to predict values, then gather the predicted values in Java.
>
> The problem is that I do not know how to re-use the model saved using the
> write.svm() function, since there is no read.svm() function.
> I read the following message in the mailing archive, stating that I may use
> the save and load methods built in R :
> http://www.mail-archive.com/r-help at r-project.org/msg64428.html
>
> Still, I am not sure how to pre-process the data and to post-process the
> results.
> Since write.svm() writes .scale and .ysale files as well as an svm file, I
> figure that the scaling data is included in the svm object.
>
> Does that mean that I do not have to worry about scaling my data and
> unscaling the results provided by the predict function on a model reloaded
> using save/load ?
> I am asking this because I previously succeeded in loading the svm model
> from libsvm in Java, but the results using unscaled data were obviously
> wrong.
I think you'll find it helpful (and enlightening) to peruse the source
code of the svm stuffs in e1071.

Start with the `svm.default` function: you'll see where the scale
attributes are calculated (and stored) in the returned object.

Then take a peak at the `predict.svm` function. You'll find if and
when any scaling is performed on the `newdata` object you are trying
to predict labels on.

In short, things should "just work" if you save/load the svm object
you've previously learned as long as your `newdata` object maintains
the same structure your training data had (number and type of features
(and column names if you're using the formula interface, I guess)).

HTH,
-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