Difference between revisions of "Logging network weights"
From Artificial Neural Network for PHP
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== Logging network weights while training == |
== Logging network weights while training == |
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− | |||
− | THIS EXAMPLE IS NOT UP TO DATE. PLEASE HAVE A LOOK TO XOR EXAMPLE!!! |
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<source lang="php"> |
<source lang="php"> |
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− | require_once 'ANN/ |
+ | require_once 'ANN/Loader.php'; |
+ | |||
+ | use ANN\Network; |
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+ | use ANN\Values; |
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try |
try |
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{ |
{ |
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− | $objNetwork = |
+ | $objNetwork = Network::loadFromFile('xor.dat'); |
} |
} |
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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 |
+ | $objNetwork = new Network; |
− | $objValues = new |
+ | $objValues = new Values; |
$objValues->train() |
$objValues->train() |
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try |
try |
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{ |
{ |
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− | $objValues = |
+ | $objValues = Values::loadFromFile('values_xor.dat'); |
} |
} |
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catch(Exception $e) |
catch(Exception $e) |
Latest revision as of 14:13, 1 June 2011
Logging network weights while 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
$objNetwork->logWeightsToFile('network.csv'); // Start logging
$objNetwork->train();
$objNetwork->saveToFile('xor.dat');