Logical XOR function: Difference between revisions
From Artificial Neural Network for PHP
Line 6: | Line 6: | ||
try |
try |
||
{ |
{ |
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$ |
$objNetwork = ANN_Network::loadFromFile('xor.dat'); |
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} |
} |
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catch(Exception $e) |
catch(Exception $e) |
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print 'Creating a new one...'; |
print 'Creating a new one...'; |
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$ |
$objNetwork = new ANN_Network; |
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} |
} |
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$ |
$arrInputs = array( |
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array(0, 0), |
array(0, 0), |
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array(0, 1), |
array(0, 1), |
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Line 22: | Line 22: | ||
); |
); |
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$ |
$arrOutputs = array( |
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array(0), |
array(0), |
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array(1), |
array(1), |
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Line 29: | Line 29: | ||
); |
); |
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$ |
$objNetwork ->setInputs($arrInputs); |
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$ |
$objNetwork ->setOutputs($arrOutputs); |
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$ |
$objNetwork ->train(); |
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$ |
$objNetwork ->saveToFile('xor.dat'); |
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</source> |
</source> |
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Revision as of 12:41, 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;
}
$arrInputs = array(
array(0, 0),
array(0, 1),
array(1, 0),
array(1, 1)
);
$arrOutputs = array(
array(0),
array(1),
array(1),
array(0)
);
$objNetwork ->setInputs($arrInputs);
$objNetwork ->setOutputs($arrOutputs);
$objNetwork ->train();
$objNetwork ->saveToFile('xor.dat');
Using trained network
require_once 'ANN/ANN_Loader.php';
try
{
$network = ANN_Network::loadFromFile('xor.dat');
}
catch(Exception $e)
{
die('Network not found');
}
$inputs = array(
array(0, 0),
array(0, 1),
array(1, 0),
array(1, 1)
);
$network->setInputs($inputs);
print_r($network->getOutputs());