Nothing
monmlp.nlm <-
function(x, y, hidden1, hidden2=0, iter.max=5000, n.trials=1,
Th=tansig, To=linear, Th.prime=tansig.prime, To.prime=linear.prime,
monotone=NULL, init.weights=NULL, max.exceptions=10,
silent=FALSE, method='BFGS', control=list(trace=0))
{
control$follow.on <- TRUE
cost.best <- Inf
for (i in seq(n.trials)){
exception <- TRUE
n.exceptions <- 0
while (exception){
exception <- FALSE
if ((length(init.weights)==2) || is.null(init.weights)){
weights <- monmlp.initialize(x=x, y=y, hidden1=hidden1,
hidden2=hidden2, init.weights=init.weights)
} else{
weights <- init.weights
}
output.mlp <- try(suppressWarnings(optimx(par=weights,
fn=monmlp.cost, gr=monmlp.grad, method=method,
itnmax=iter.max, control=control, xx=x, yy=y,
hidden1=hidden1, hidden2=hidden2, Th=Th, To=To,
Th.prime=Th.prime, To.prime=To.prime,
monotone=monotone)),
silent=FALSE)
if (class(output.mlp)[[1]]=="try-error"){
exception <- TRUE
n.exceptions <- n.exceptions + 1
if (n.exceptions > max.exceptions)
stop("maximum number of exceptions reached")
}
}
output.mlp <- output.mlp[nrow(output.mlp),]
weights <- unlist(output.mlp[seq_along(weights)])
code <- output.mlp$conv
cost <- output.mlp$value
if(!silent) cat(cost, '\n')
if (cost < cost.best){
weights.best <- weights
cost.best <- cost
code.best <- code
}
}
list(weights=weights.best, cost=cost.best, code=code.best)
}
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