Am Montag, den 08.06.2009, 18:20 +0200 schrieb Juergen Rose:
> Hello,
>
> In the attached file training.csv (I apologize for the large file) I
> have 238 objects belonging to 13 classes, which are described by 183
> properties. I would like to find a svm model for these objects.
>
> I tried the following R statements.
>
> library('e1071')
> datatraining <- read.csv("training.csv",head=TRUE)
>
> names<-names(datatraining)
> print("before print(names)"); print(names)
> # There are 186 names, respectively 184 properties P3, P4 ... P1549
>
> data <- subset(datatraining,select=c(-dataname_gen_spec,-Gen))
> classes <- subset(datatraining,select=Gen)
> # There are 13 classes
>
> model <- svm(data,classes,type='C-classification',kernel='linear')
> print(sprintf("There are %d support vectors",model$tot.nSV));
> # There are 176 support vectors
>
> print("before summary(model)"); summary(model)
> $index);
> print("before print(model$index)"); print(model$index);
>
>
> I expect that the index values are between 1 and 184, because there are
> 84 properties, but I get several indices larger than 200. What did I
> misunderstood?
>
> Any hint is very appreciated.
>
> Regards Juergen
Hi, once again, I just recognized, that the support vectors are objects and not
properties.
So that my last question was nonsense. But the reason for my question
was, that I would like to get the important properties from a svm model.
Is there any way?
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