#include #include "genann.h" int main(int argc, char *argv[]) { printf("GENANN example 1.\n"); printf("Train a small ANN to the XOR function using backpropagation.\n"); /* Input and expected out data for the XOR function. */ const double input[4][2] = {{0, 0}, {0, 1}, {1, 0}, {1, 1}}; const double output[4] = {0, 1, 1, 0}; int i; /* New network with 2 inputs, * 1 hidden layer of 2 neurons, * and 1 output. */ genann *ann = genann_init(2, 1, 2, 1); /* Train on the four labeled data points many times. */ for (i = 0; i < 300; ++i) { genann_train(ann, input[0], output + 0, 3); genann_train(ann, input[1], output + 1, 3); genann_train(ann, input[2], output + 2, 3); genann_train(ann, input[3], output + 3, 3); } /* Run the network and see what it predicts. */ printf("Output for [%1.f, %1.f] is %1.f.\n", input[0][0], input[0][1], *genann_run(ann, input[0])); printf("Output for [%1.f, %1.f] is %1.f.\n", input[1][0], input[1][1], *genann_run(ann, input[1])); printf("Output for [%1.f, %1.f] is %1.f.\n", input[2][0], input[2][1], *genann_run(ann, input[2])); printf("Output for [%1.f, %1.f] is %1.f.\n", input[3][0], input[3][1], *genann_run(ann, input[3])); genann_free(ann); return 0; }