Logical XOR function

Revision as of 13:29, 1 June 2011 by Thwien (talk | contribs) (Using trained network)
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FAQ

For information about dat-files have a view to the FAQ page.

Training

require_once 'ANN/Loader.php';

use ANN\Network;
use ANN\Values;

try
{
  $objNetwork = Network::loadFromFile('xor.dat');
}
catch(Exception $e)
{
  print 'Creating a new one...';
	
  $objNetwork = new Network;

  $objValues = new Values;

  $objValues->train()
            ->input(0,0)->output(0)
            ->input(0,1)->output(1)
            ->input(1,0)->output(1)
            ->input(1,1)->output(0);

  $objValues->saveToFile('values_xor.dat');
  
  unset($objValues);
}

try
{
  $objValues = Values::loadFromFile('values_xor.dat');
}
catch(Exception $e)
{
  die('Loading of values failed');
}

$objNetwork->setValues($objValues); // to be called as of version 2.0.6

$boolTrained = $objNetwork->train();

print ($boolTrained)
        ? 'Network trained'
        : 'Network not trained completely. Please re-run the script';

$objNetwork->saveToFile('xor.dat');

$objNetwork->printNetwork();

Using trained network

require_once 'ANN/Loader.php';

use ANN\Network;
use ANN\Values;

try
{
  $objNetwork = Network::loadFromFile('xor.dat');
}
catch(Exception $e)
{
  die('Network not found');
}

try
{
  $objValues = Values::loadFromFile('values_xor.dat');
}
catch(Exception $e)
{
  die('Loading of values failed');
}

$objValues->input(0, 1)  // input values appending the loaded ones
          ->input(1, 1)
          ->input(1, 0)
          ->input(0, 0)
          ->input(0, 1)
          ->input(1, 1);

$objNetwork->setValues($objValues);

print_r($objNetwork->getOutputs());