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]] > > ______________________________________________ > 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. ______________________________________________ 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.
