Hi Thomas,
On Wed, Mar 14, 2012 at 11:00 AM, Thomas Coffin
thomas.cof...@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@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
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