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XOR training

This example shows how to train data for XOR function

Example #1 xor.data file

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

Example #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);
}
?>

This example shows how to read and run data for XOR function

Example #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);
?>

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User Contributed Notes 3 notes

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68
Aurelien Marchand
10 years ago
Here is an explanation for the input file for training, as it might be obvious to everyone and you must understand it to write your own:

4 2 1 <- header file saying there are 4 sets to read, with 2 inputs and 1 output
-1 -1 <- the 2 inputs for the 1st group
-1 <- the 1 output for the 1st group
-1 1 <- the 2 inputs for the 2nd group
1 <- the 1 output for the 2nd group
1 -1 <- the 2 inputs for the 3rd group
1 <- the 1 output for the 3rd group
1 1 <- the 2 inputs for the 4th group
-1 <- the 1 output for the 4th group
up
1
ithirzty
5 years ago
If you wan't your result to be saved after the time limit, you will need to add this to your code.
<?php
function shutdown()
{
global
$ann;
fann_save($ann, dirname(__FILE__) . "/result.net");
fann_destroy($ann);
}

register_shutdown_function('shutdown');
?>
where $ann is your neural network var and 'result.net' your neural network config file.
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