Displaying 1 result from an estimated 1 matches for "newdata_classes".
2010 May 14
0
bootstrapping an svm
...sv", header=T)
E <- read.csv("CLStest.csv", header=T)
dataclstraining <- subset(D,select=c(....))
classesclstraining <- subset(D, select=Class)
dataclstest <- subset(E,select=c(.......))
classesclstest <- subset(E, select=Class)
bootsvm <- function(data, new_data, newdata_classes, indices)
{
d <-data[indices,]
** model2 <- best.svm(Class~.,data=d, gamma = 10^(-6:-1), cost = 10^(-1:1), tunecontrol=tune.control(sampling="bootstrap", nboot=1000, boot.size=8/8))
pred.b <- predict(model2, newdata=new_data, decision.values=FALSE, probability=FALSE)
return(a...