Usage
mlp_teach_rprop(net, input, output, tol_level, max_epochs, l2reg = 0, u = 1.2, d = 0.5, gmax = 50, gmin = 1e-06, report_freq = 0)
Arguments
net
an object of mlp_net class
input
numeric matrix, each row corresponds to one input vector,
the number of columns must be equal to the number of neurons
in the network input layer
output
numeric matrix with rows corresponding to expected outputs,
the number of columns must be equal to the number of neurons
in the network output layer, the number of rows must be equal to the number
of input rows
tol_level
numeric value, error (MSE) tolerance level
max_epochs
integer value, maximal number of epochs (iterations)
l2reg
numeric value, L2 regularization parameter (default 0)
u
numeric value, Rprop algorithm parameter (default 1.2)
d
numeric value, Rprop algorithm parameter (default 0.5)
gmax
numeric value, Rprop algorithm parameter (default 50)
gmin
numeric value, Rprop algorithm parameter (default 1e-6)
report_freq
integer value, progress report frequency, if set to 0 no information is printed
on the console (this is the default)