FANN XOR training

이 예제에서는 XOR 함수에 대한 데이터를 훈련하는 방법을 보여줍니다.

예제 #1 xor.data file

                  
4 2 1
-1 -1
-1
-1 1
1
1 -1
1
1 1
-1
                  
                

예제 #2 Simple train

                  
<?php
$num_input = 2;
$num_output = 1;
$num_layers = 3;
$num_neurons_hidden = 3;
$desired_error = 0.001;
$max_epochs = 500000;
$epochs_between_reports = 1000;

$ann = fann_create_standard($num_layers, $num_input, $num_neurons_hidden, $num_output);

if ($ann) {
    fann_set_activation_function_hidden($ann, FANN_SIGMOID_SYMMETRIC);
    fann_set_activation_function_output($ann, FANN_SIGMOID_SYMMETRIC);

    $filename = dirname(__FILE__) . "/xor.data";
    if (fann_train_on_file($ann, $filename, $max_epochs, $epochs_between_reports, $desired_error))
        fann_save($ann, dirname(__FILE__) . "/xor_float.net");

    fann_destroy($ann);
}
?>
                  
                

이 예제는 XOR 함수에 대한 데이터를 읽고 실행하는 방법을 보여줍니다.

예제 #3 Simple test

                  
<?php
$train_file = (dirname(__FILE__) . "/xor_float.net");
if (!is_file($train_file))
    die("The file xor_float.net has not been created! Please run simple_train.php to generate it");

$ann = fann_create_from_file($train_file);
if (!$ann)
    die("ANN could not be created");

$input = array(-1, 1);
$calc_out = fann_run($ann, $input);
printf("xor test (%f,%f) -> %f\n", $input[0], $input[1], $calc_out[0]);
fann_destroy($ann);
?>