Interpreting predictions of svm
You should give us the data is what you should do :) Aside from that: you can only make probability predictions if you activated it when making the model.
On 07.08.2012, at 17:23, Camomille wrote:
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]]
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