[R] SVM Param Tuning with using SNOW package

[raluca]

Hello,

Is the first time I am using SNOW package and I am trying to tune the cost
parameter for a linear SVM, where the cost (variable cost1) takes 10 values
between 0.5 and 30.

I have a large dataset and a pc which is not very powerful, so I need to
tune the parameters using both CPUs of the pc.

Somehow I cannot manage to do it. It seems that both CPUs are fitting the
model for the same values of cost1, I guess the first 5, but not for the
last 5.

Please, can anyone help me! :-((

Here is the code:  

data <- data.frame(Y=I(Y),X=I(X))
data.X<-data$X
data.Y<-data$Y

NR=10
cost1=seq(0.5,30, length=NR)

sv.lin<- function(cl,c) {

for (i in 1:NR) {

ind=sample(1:414,276)

hogTest<-  data.frame(Y=I(data.Y[-ind]),X=I(data.X[-ind,])) 
hogTrain<- data.frame(Y=I(data.Y[ind]),X=I(data.X[ind,])) 

svm.lin   	  <- svm(hogTrain$X,hogTrain$Y, kernel="linear",cost=c[i],
cross=5)
results.lin   <- predict(svm.lin, hogTest$X)

e.test.lin     <- sqrt(sum((results.lin-hogTest$Y)^2)/length(hogTest$Y))

return(e.test.lin)
}
}

cl<- makeCluster(10, type="SOCK" ) 

clusterEvalQ(cl,library(e1071))

clusterExport(cl,c("data.X","data.Y","NR","cost1")) 

RMSEP<-clusterApplyLB(cl,cost1,sv.lin)

stopCluster(cl)


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