R help - Feb 2010 - e1071: Cannot predict probabilities

Dear list.

I using the SVM-methods from the e1071, but I can't get the
probabilities when predicting.

Code:
x <- matrix(rbinom(100, 10, 0.3), ncol=2)
y <- apply(x, 1, sum)
fit <- svm(y ~ x, method = "C-classification", kernel =
"radial",
probability = TRUE)
predict(fit, x, probability=TRUE)

Here predict doesn't containing any probabilities (not as attributes
either). Does anybody know what I'm doing wrong or if the package
contains any bugs?

version.string R version 2.9.2 (2009-08-24)
Version of the e1071-package: 1.5-21

Cheers, Mikkel.

Hi,

On Tue, Feb 23, 2010 at 2:43 PM, Mikkel Meyer Andersen <r at mikl.dk>
wrote:
> Dear list.
>
> I using the SVM-methods from the e1071, but I can't get the
> probabilities when predicting.
>
> Code:
> x <- matrix(rbinom(100, 10, 0.3), ncol=2)
> y <- apply(x, 1, sum)
> fit <- svm(y ~ x, method = "C-classification", kernel =
"radial",
> probability = TRUE)
> predict(fit, x, probability=TRUE)
>
> Here predict doesn't containing any probabilities (not as attributes
> either). Does anybody know what I'm doing wrong or if the package
> contains any bugs?
Look at your "fit" object, specifically the SVM-Type and notice that
you are actually running eps-regression, even though you try to
specify classification. So  the type of "probabilities" you're
after
don't really make sense in regression context.

A "better" posed problem definition will give you what you're
after. I
mean, by just running your  example code, my y vector has 10 different
(unique) labels (yours maybe different do to your random seed, I
guess) -- but are you really trying to do 10-way classification?

-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