I have carefully read the CARET documentation at: http://caret.r-forge.r-project.org/training.html, the vignettes, and everything is quite clear (the examples on the website hel
If you are not sure what role method plays if you use index, why not to apply all the methods and compare results. It is a blind method of comparaison, but it can give you some intuitions.
methods <- c('boot', 'boot632', 'cv',
'repeatedcv', 'LOOCV', 'LGOCV')
I create my index:
n <- 100
tmp <- createDataPartition(logBBB,p = .8, times = n)
I apply trainControl
for my list of method, and I remove index from result since it is common to all my methods.
ll <- lapply(methods,function(x)
trControl = trainControl(method = x, index = tmp))
ll <- sapply(ll,'[<-','index', NULL)
Hence my ll is :
[,1] [,2] [,3] [,4] [,5] [,6]
method "boot" "boot632" "cv" "repeatedcv" "LOOCV" "LGOCV"
number 25 25 10 10 25 25
repeats 25 25 1 1 25 25
verboseIter FALSE FALSE FALSE FALSE FALSE FALSE
returnData TRUE TRUE TRUE TRUE TRUE TRUE
returnResamp "final" "final" "final" "final" "final" "final"
savePredictions FALSE FALSE FALSE FALSE FALSE FALSE
p 0.75 0.75 0.75 0.75 0.75 0.75
classProbs FALSE FALSE FALSE FALSE FALSE FALSE
summaryFunction ? ? ? ? ? ?
selectionFunction "best" "best" "best" "best" "best" "best"
preProcOptions List,3 List,3 List,3 List,3 List,3 List,3
custom NULL NULL NULL NULL NULL NULL
timingSamps 0 0 0 0 0 0
predictionBounds Logical,2 Logical,2 Logical,2 Logical,2 Logical,2 Logical,2