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#include "fann.h"
int main( int argc, char** argv )
{
const unsigned int num_input = 3;
const unsigned int num_output = 1;
const unsigned int num_layers = 4;
const unsigned int num_neurons_hidden = 5;
const float desired_error = (const float) 0.0001;
const unsigned int max_epochs = 5000;
const unsigned int epochs_between_reports = 1000;
struct fann_train_data * data = NULL;
struct fann *ann = fann_create_standard(num_layers, num_input, num_neurons_hidden, num_neurons_hidden, num_output);
fann_set_activation_function_hidden(ann, FANN_SIGMOID_SYMMETRIC);
fann_set_activation_function_output(ann, FANN_LINEAR);
fann_set_training_algorithm(ann, FANN_TRAIN_RPROP);
data = fann_read_train_from_file( "scaling.data" );
/* Just pass any param to perform scaling */
if( argc > 1 )
{
fann_set_scaling_params(
ann,
data,
-1, /* New input minimum */
1, /* New input maximum */
-1, /* New output minimum */
1); /* New output maximum */
fann_scale_train( ann, data );
/*
fann_save_train(data, "scaled_scaling.data");
fann_descale_train( ann, data );
fann_save_train(data, "descaled_scaling.data");
*/
}
fann_train_on_data(ann, data, max_epochs, epochs_between_reports, desired_error);
free( data );
fann_save(ann, "scaling.net");
fann_destroy(ann);
return 0;
}
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