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
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