Logical XOR function: Difference between revisions

From Artificial Neural Network for PHP
Line 13: Line 13:
$objNetwork = new ANN_Network;
$objNetwork = new ANN_Network;
}


$objValues = new ANN_Values;
$arrInputs = array(
array(0, 0),
array(0, 1),
array(1, 0),
array(1, 1)
);


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


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

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


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


$objNetwork->train();
$objNetwork->train();

Revision as of 17:51, 18 December 2008

Training

require_once 'ANN/ANN_Loader.php';

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

  $objValues = new ANN_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 = ANN_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

$objNetwork->train();

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

Using trained network

require_once 'ANN/ANN_Loader.php';

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

$arrInputs = array(
	array(0, 0),
	array(0, 1),
	array(1, 0),
	array(1, 1)
);

$objNetwork->setInputs($arrInputs);

print_r($objNetwork->getOutputs());