Hi, I have some difficulties in interpreting the prediction of a svm model
using the package e1071.
y1 is the variable I want to predict. It is of type factor and has got two
levels: "< 50%" and "> 50%".
z is the dataset.
> model <- svm(y1 ~ ., data = z,type="C-classification", cross=10)
> model
Call:
svm(formula = y1 ~ ., data = z, type = "C-classification", cross = 10)
Parameters:
SVM-Type: C-classification
SVM-Kernel: radial
cost: 1
gamma: 0.07142857
Number of Support Vectors: 68
> pred <- predict(model,newdata=z,probability=TRUE,decision.values = TRUE)
> table(pred)
pred
< 50% > 50%
414 0
The results of "pred" is not what I intended to get as, I expected this
type of result:
< 50% > 50%
< 50% 89 25
> 50% 38 262
What should I do?
--
View this message in context:
http://r.789695.n4.nabble.com/Interpreting-predictions-of-svm-tp4639405.html
Sent from the R help mailing list archive at Nabble.com.
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
