mlff_initialize_weights
Initializes weights for multilayered feedforward neural networks prior to network training using one of four user selected methods.
Synopsis
#include <imsls.h>
float *imsls_f_mlff_initialize_weights (Imsls_f_NN_Network *network, int n_patterns, int n_nominal, int n_continuous, int nominal[], float continuous[], ..., 0)
The type double function is imsls_d_mlff_initialize_weights.
Required Arguments
Imsls_f_NN_Network *network (Input/Output)
Pointer to a structure of type
Imsls_f_NN_Network containing the parameters that define the feedforward network’s architecture, including network weights and bias values. For more details, see
imsls_f_mlff_network. When network training is successful, the weights and bias values in
network are replaced with the values calculated for the optimum trained network.
int n_patterns (Input)
Number of training patterns.
int n_nominal (Input)
Number of unencoded nominal attributes.
int nominal[] (Input)
Array of size n_patterns by n_nominal containing the nominal input variables.
int n_continuous (Input)
Number of continuous attributes, including ordinal attributes encoded using cumulative percentage.
float continuous[] (Input)
Array of size n_patterns by n_continuous containing the continuous and scaled ordinal input variables.
Return Value
Pointer to an array of length
network->n_links + (
network->n_nodes-network->n_inputs) containing the initialized weights. See the
Description section for details on weight ordering. This space can be released by using the
imsls_free function.
