I am using the train() function of caret package with method='nnet', and I have registered 6 cores using doMC. But it uses only one core.
This is my code:
library(caret)
library(foreach)
library(doMC)
registerDoMC(cores = 6)
.... some code...
nnmodel.grid <- expand.grid(.size=c(100,50))
myTrainControl = trainControl(allowParallel=TRUE)
nnmodel.fit <- train(formulaForNN, data = trainingdata, method = "nnet", tuneGrid =
nnmodel.grid, trControl = myTrainControl)
Though the answer at this link shows that all the registered core can be used. The only difference I can see is
tc <- trainControl(method="boot",number=25)
i.e. he uses a 'boot' method for resampling.
Does that means caret only uses multicore for resampling, and without using any resampling techniques we can't train neural networks in parallel ?
