FCNN4R (version 0.6.2)

mlp_teach_rprop: Rprop teaching

Description

Rprop is a fast and robust adaptive step method based on backpropagation. For details, please refer to the original paper given in References section.

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)

Value

Two-element list, the first field (net) contains the trained network, the second (mse) - the learning history (MSE in consecutive epochs).

References

M. Riedmiller. Rprop - Description and Implementation Details: Technical Report. Inst. f. Logik, Komplexitat u. Deduktionssysteme, 1994.