[R] Predict function for 'newdata' of different dimension in svm

[David Meyer]

Sandra,

hard to tell where the error message originates from without having the data
at hand (perhaps you could provide that to me off-list?), but I am almost
sure things will work when you train the model the "standard" way:

cd1.svm<-svm(Acode~EXT+TOF, data = boot.dist.dat, cost=100, gamma=20)

and then do the predictions.

Best,
David

-------------------------
I am using the "predict" function on a support vector machine (svm)
object, and I don't understand why I can't predict on a dataset with more
observations than the training dataset.

I think this problem is a generic "predict" problem, but I'm not sure.

The original svm was fit on 50 observations.

cd1.svm<-svm(boot.dist.dat$Acode~boot.dist.dat$EXT+boot.dist.dat
$TOF,cost=100,gamma=20)

## for these training data,
> names(boot.dist.dat)
[1] "TOF"   "EXT"   "Acode"
> dim(boot.dist.dat)
[1] 50  3

Now I want to use the svm classifier on a new dataset with 175
observations:

new.dat<-data.frame(TOF=Cd1[cand.adult,]$TOF,EXT=Cd1[cand.adult,]
$EXT,Acode=rep(0,175),row.names=NULL)

## for the new dataset,
> names(new.dat)
[1] "TOF"   "EXT"   "Acode"
> dim(new.dat)
[1] 175   3

Now try to predict:

> predict(cd1.svm,newdata=new.dat)

Error in "names<-.default"(`*tmp*`, value = c("1", "2", "3", "4", "5",  :
        'names' attribute [175] must be the same length as the vector [50]

What am I missing?  Why would the row names have to be the same?

Thanks so much,
Sandra McBride
-- 
Dr. David Meyer
Department of Information Systems and Operations

Vienna University of Economics and Business Administration
Augasse 2-6, A-1090 Wien, Austria, Europe
Tel: +43-1-313 36 4393
Fax: +43-1-313 36 90 4393 
HP:  http://wi.wu-wien.ac.at/~meyer/