<?php
namespace MachineLearning;
include 'Util/Input.php';
include 'Util/Output.php';
$numLayers = 3;
$numInput = Util\Input::NUM_INPUT;
$numNeuronsHidden = 9;
$numOutput = Util\Output::NUM_OUTPUT;
$maxEpochs = 500000;
$epochsBetweenReports = 1000;
$desiredError = 0.001;
$ann = fann_create_standard($numLayers, $numInput, $numNeuronsHidden, $numOutput);
if ($ann) {
fann_set_activation_function_hidden($ann, FANN_SIGMOID_SYMMETRIC);
fann_set_activation_function_output($ann, FANN_SIGMOID_SYMMETRIC);
if (fann_train_on_file($ann, 'Data/training', $maxEpochs, $epochsBetweenReports, $desiredError)) {
fann_save($ann, 'Data/training_result');
}
fann_destroy($ann);
}
/**
* Save ANN to file
* @param string filename with absolute path
* @return bool true on success, false on error
*/
public function save($filename)
{
$this->checkIfAnnIsAssigned();
return fann_save($this->annId, $filename);
}
<?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);
}
/**
* Save.
*
* @return bool
*/
public function save()
{
$result = fann_save($this->ann, $this->configurationFile);
return $result;
}
*
* If you have any questions or comments, please e-mail Evan Nemerson
* <*****@*****.**>
*/
/* If you don't want to compile FANN into PHP... */
if (!extension_loaded('fann')) {
if (!dl('fann.so')) {
exit("You must install the FANN extension. You can get it from http://fann.sf.net/\n");
}
}
/* Create an artificial neural network */
$ann = fann_create(array(2, 4, 1), 1.0, 0.7);
/* To load from a file, you can use. If your version of PHP includes the streams API (4.3.0+ ?),
* this can be anything accessible through streams (http, ftp, https, etc) */
// $ann = fann_create("http://example.com/xor_float.net");
/* Train the network using the same data as is in the xor.data file */
fann_train($ann, array(array(array(0, 0), array(0)), array(array(0, 1), array(1)), array(array(1, 0), array(1)), array(array(1, 1), array(0))), 100000, 1.0E-5, 1000);
/* To achieve the same effect as the above with the data stored in an external file... Also works
* with the streams API, when available. */
// fann_train($ann, '/home/tadpole/local/src/fann/examples/xor.data', 100000, 0.00001, 1000);
print_r(fann_run($ann, array(0, 0)));
// Should be ~ 0
print_r(fann_run($ann, array(0, 1)));
// Should be ~ 1
print_r(fann_run($ann, array(1, 0)));
// Should be ~ 1
print_r(fann_run($ann, array(1, 1)));
// Should be ~ 0
/* This function is pretty simple. It will use the streams API if available. */
fann_save($ann, 'xor_float.net');
public function save()
{
fann_save($this->ann, $this->file);
}
