Regarding nnet package's optimization method 'BFGS'

Machine Learning and Modeling
1

Hello everyone,

I am using nnet in caret. The nnet document shows that the package uses BFGS optimization method (page no. 5, last line of documentation).

  1. Where can find the details the BFGS, particularly the learning rate/step size?
  2. How is it different from optimization method in Keras R such as SGD, adam, rmsprop ?

Thanks

myControl <- caret::trainControl(## n-fold CV
method = "repeatedcv",
number = 5,
repeats = 1,
verboseIter = TRUE)

nnGrid <- expand.grid(size =5,
decay = seq(0, 0.6, 0.1))

nnetFit <- caret::train(choice ~ .,
data = tbl,
method = "nnet",
tuneGrid = nnGrid,
trace = FALSE,
maxit = 1000,
trControl = myControl)

2

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