Displaying 2 results from an estimated 2 matches for "rbfsvm".
2012 Nov 23
1
caret train and trainControl
...hen pass your tunings to train.
It seems with caret, tuning and training are both handled by train.
I am using train and trainControl to find my hyper parameters like so:
MyTrainControl=trainControl(
method = "cv",
number=5,
returnResamp = "all",
classProbs = TRUE
)
rbfSVM <- train(label~., data = trainset,
method="svmRadial",
tuneGrid = expand.grid(.sigma=c(0.0118),.C=c(8,16,32,64,128)),
trControl=MyTrainControl,
fit = FALSE
)
Once this returns my ideal parameters, in this c...
2012 Nov 29
1
Help with this error "kernlab class probability calculations failed; returning NAs"
...ex, trunc(length(index)*30/100))
trainset <- dataset[-testindex,]
testset <- dataset[testindex,-1]
## TUNE caret / kernlab
set.seed(1)
MyTrainControl=trainControl(
method = "repeatedcv",
number=10,
repeats=5,
returnResamp = "all",
classProbs = TRUE
)
## MODEL
rbfSVM <- train(outcome~., data = trainset,
method="svmRadial",
preProc = c("scale"),
tuneLength = 10,
trControl=MyTrainControl,
fit = FALSE
)
There were 50 or more warnings (use warnings()...