FANN xor_test - eiichiromomma/CVMLAB GitHub Wiki
(FANN) xor_test
XORのテスト
#include <stdio.h>
#include "fann.h"
int main()
{
fann_type *calc_out;
unsigned int i;
int ret = 0;
struct fann *ann;
struct fann_train_data *data;
printf("Creating network.\n");
//ネットワークの読み込み(ファイルから)
ann = fann_create_from_file("xor_float.net");
//エラー処理
if(!ann)
{
printf("Error creating ann --- ABORTING.\n");
return 0;
}
//接続状態の表示
fann_print_connections(ann);
//パラメータの表示
fann_print_parameters(ann);
printf("Testing network.\n");
//テストデータの読み込み(ファイルから)
data = fann_read_train_from_file("xor.data");
for(i = 0; i < fann_length_train_data(data); i++)
{
//誤差のリセット
fann_reset_MSE(ann);
//テストの実行
calc_out = fann_test(ann, data->input[i], data->output[i]);
printf("XOR test (%f, %f) -> %f, should be %f, difference=%f\n",
data->input[i][0], data->input[i][1], calc_out[0], data->output[i][0],
(float) fann_abs(calc_out[0] - data->output[i][0]));
}
//後片付け
printf("Cleaning up.\n");
fann_destroy_train(data);
fann_destroy(ann);
return ret;
}Creating network.
Layer / Neuron 0123456
L 1 / N 3 CCc....
L 1 / N 4 CCC....
L 1 / N 5 CCC....
L 1 / N 6 .......
L 2 / N 7 ...dBBd
L 2 / N 8 .......
Input layer : 2 neurons, 1 bias
Hidden layer : 3 neurons, 1 bias
Output layer : 1 neurons
Total neurons and biases : 8
Total connections : 13
Connection rate : 1.000
Shortcut connections : 0
Training algorithm : FANN_TRAIN_RPROP
Training error function : FANN_ERRORFUNC_TANH
Training stop function : FANN_STOPFUNC_BIT
Learning rate : 0.700
Learning momentum : 0.000
Quickprop decay : -0.000100
Quickprop mu : 1.750
RPROP increase factor : 1.200
RPROP decrease factor : 0.500
RPROP delta min : 0.000
RPROP delta max : 50.000
Cascade output change fraction : 0.010000
Cascade candidate change fraction : 0.010000
Cascade output stagnation epochs : 12
Cascade candidate stagnation epochs : 12
Cascade max output epochs : 150
Cascade max candidate epochs : 150
Cascade weight multiplier : 0.400
Cascade candidate limit :1000.000
Cascade activation functions[0] : FANN_SIGMOID
Cascade activation functions[1] : FANN_SIGMOID_SYMMETRIC
Cascade activation functions[2] : FANN_GAUSSIAN
Cascade activation functions[3] : FANN_GAUSSIAN_SYMMETRIC
Cascade activation functions[4] : FANN_ELLIOT
Cascade activation functions[5] : FANN_ELLIOT_SYMMETRIC
Cascade activation steepnesses[0] : 0.250
Cascade activation steepnesses[1] : 0.500
Cascade activation steepnesses[2] : 0.750
Cascade activation steepnesses[3] : 1.000
Cascade candidate groups : 2
Cascade no. of candidates : 48
Testing network.
XOR test (-1.000000, -1.000000) -> -0.982257, should be -1.000000, difference=0.017743
XOR test (-1.000000, 1.000000) -> 0.990769, should be 1.000000, difference=0.009231
XOR test (1.000000, -1.000000) -> 0.991142, should be 1.000000, difference=0.008858
XOR test (1.000000, 1.000000) -> -0.988301, should be -1.000000, difference=0.011699
Cleaning up.
重みが均等にかかっている。たまたま上手くいった。