> Finally figured it out.  You have to extract it from the attributes.
> Tricky.  Thanks anyway.

> attr(pred, "prob")[1:10,]

Correct. 

Just for the records, the rationale behind this `tricky' design:

In addition to probabilites, predict.svm() (more precisely: libsvm) can also 
compute the decision values. Common ways to handle `polymorph' prediction types 
are, e.g, using a `type' argument in the predict() function, or to return all 
variants in one list object. With a `type' argument, you need several calls to 
predict() if you need, say, hard predictions _and_ the probabilities. On the 
other hand, the probability and decision values features were added to libsvm 
only when svm() in e1071 had already been around for a while, so returning a 
list instead of a vector would have broken a lot of code. So I decided to keep 
the `standard' predict behavior and to `hide' special predictions in an 
attribute. If the latter had been available from the beginning, I probably 
would have used the `type' approach.

Cheers,
David


On 2/16/06, roger bos <[EMAIL PROTECTED]> wrote:
>
> I am using SVM to classify categorical data and I would like the
> probabilities instead of the classification.  ?predict.svm says that its
> only enabled when you train the model with it enabled, so I did that, but it
> didn't work.  I can't even get it to work with iris.  The help file shows
> that probability = TRUE when training the model, but doesn't show an
> example.  Then I try to predict with probabilities, I still only get
> classifications back.  Anyone get this to work and can help me out?

-- 
Dr. David Meyer
Department of Information Systems and Operations

Vienna University of Economics and Business Administration
Augasse 2-6, A-1090 Wien, Austria, Europe
Fax: +43-1-313 36x746 
Tel: +43-1-313 36x4393
HP:  http://wi.wu-wien.ac.at/~meyer/

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