Hi all,
I'm using SVM to classify data (2 classes) and I get strange results :
> model = svm(x, y, probability = TRUE)
> pred = predict(model, x, decision.values = TRUE, probability = FALSE)
> table(pred,y)
y
pred ctl nuc
ctl 82 3
nuc 5 84
> pred
1 2 3 4 5 6 7 8 ....
nuc nuc nuc nuc nuc nuc nuc ctl ....
And now, with probabities computation :
> pred = predict(model, x, decision.values = TRUE, probability = TRUE)
> table(pred,y)
y
pred ctl nuc
ctl 7 84
nuc 80 3
> pred
1 2 3 4 5 6 7 8 ....
ctl ctl ctl ctl ctl ctl ctl nuc ...
However, model, x, and y didn't change !! Also, decision.values didn't
change :
nuc/ctl
1 0.505289854
2 0.265975135
3 0.863270144
4 0.354181677
5 0.868119168
6 0.702989607
7 0.206018067
8 -0.271452937 -> ctl is correct !
....
Is it a bug ? Could you explain the difference ?
Best regards,
charles
--
Charles Hébert
DYnamique et Organisation des GENomes,
Laboratoire de Génétique Moléculaire, CNRS UMR 8541
Ecole Normale Supérieure 46, rue d'Ulm 75005 Paris, France
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