When the user modifies one or several parameters by giving them as
named arguments, if some names are incorrect they are ignored with a
warning.
The parameters with their default values are:
iterlim = 100: an integer giving the number of
iterations.
quiet = FALSE: a logical controlling whether to print
the value of the objective function at each iteration.
quasinewton = FALSE: a logical. If TRUE,
quasi-Newton steps are performed (not recommended unless the
network has a small number of parameters and/or for a small number
of iterations).
fullhessian = FALSE: (ignored if quasinewton =
FALSE) a logical, by default only some blocks of the Hessian matrix
are computed. If TRUE, the full Hessian matrix is computed
(very time consuming).
trace.error = FALSE: a logical. If TRUE, the
error rate is printed at each iteration of the optimization process.
wolfe = FALSE: a logical. If TRUE, Wolfe's
conditions are tested at each iteration.
target = 0.001: the target value of the loss function
to stop the optimization.
beta = 0.2: the hyperparameter of the activation
function.
mc.cores = 1: an integer. The number of cores used when
computing the objective function.
If mc.cores is greater than one, the optimization process calls
a multithreaded code using OMP. So, do not do this together
with functions from the package parallel. On the other hand, if
you leave this parameter to its default value, you should be able to
run several optimizations in parallel, for instance with
mclapply.
See the vignette for applications.