Using date input support class: Difference between revisions
From Artificial Neural Network for PHP
(New page: == FAQ == For information about dat-files have a view to the FAQ page. == Training == <source lang="php"> require_once 'ANN/Loader.php'; try { $objNetwork = ANN_Network::loadFro...) |
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For information about dat-files have a view to the [[FAQ]] page. |
For information about dat-files have a view to the [[FAQ]] page. |
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== XML for holidays == |
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The standard filename is ''Holidays.xml'' but can be changed by calling ANN_DateInputs::setHolidaysFilename(). |
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<source lang="xml"> |
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<?xml version="1.0" encoding="UTF-8"?> |
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<holidays> |
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<holiday> |
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<day>1</day> |
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<month>1</month> |
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<year>any</year> |
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<country>Germany</country> |
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<state>any</state> |
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<description>New Year</description> |
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</holiday> |
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<holiday> |
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<day>24</day> |
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<month>12</month> |
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<year>any</year> |
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<country>Germany</country> |
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<state>any</state> |
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<description>Christmas</description> |
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</holiday> |
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</holidays> |
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</source> |
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== Training == |
== Training == |
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$objNetwork = new ANN_Network(2, 8, 1); |
$objNetwork = new ANN_Network(2, 8, 1); |
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$objDateInput = new ANN_DateInputs('2010-01-03'); // As of ANN 2.1.3 |
$objDateInput = new ANN_DateInputs('2010-01-03'); // As of ANN 2.1.3 |
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$objTemperature = new ANN_InputValue(-15, 50); // Temperature in Celsius |
$objTemperature = new ANN_InputValue(-15, 50); // Temperature in Celsius |
Latest revision as of 18:53, 6 January 2010
FAQ
For information about dat-files have a view to the FAQ page.
XML for holidays
The standard filename is Holidays.xml but can be changed by calling ANN_DateInputs::setHolidaysFilename().
<?xml version="1.0" encoding="UTF-8"?>
<holidays>
<holiday>
<day>1</day>
<month>1</month>
<year>any</year>
<country>Germany</country>
<state>any</state>
<description>New Year</description>
</holiday>
<holiday>
<day>24</day>
<month>12</month>
<year>any</year>
<country>Germany</country>
<state>any</state>
<description>Christmas</description>
</holiday>
</holidays>
Training
require_once 'ANN/Loader.php';
try
{
$objNetwork = ANN_Network::loadFromFile('icecreams.dat');
}
catch(Exception $e)
{
print 'Creating a new one...';
$objNetwork = new ANN_Network(2, 8, 1);
$objDateInput = new ANN_DateInputs('2010-01-03'); // As of ANN 2.1.3
$objTemperature = new ANN_InputValue(-15, 50); // Temperature in Celsius
$objTemperature->saveToFile('input_temperature.dat');
$objHumidity = new ANN_InputValue(0, 100); // Humidity percentage
$objHumidity->saveToFile('input_humidity.dat');
$objIcecream = new ANN_OutputValue(0, 300); // Quantity of sold ice-creams
$objIcecream->saveToFile('output_quantity.dat');
$objValues = new ANN_Values;
$objValues->train()
->input(
$objTemperature->getInputValue(20),
$objHumidity->getInputValue(10),
$objDateInput->getHolidaysInWeek() // As of ANN 2.1.3
)
->output(
$objIcecream->getOutputValue(20)
)
->input(
$objTemperature->getInputValue(30),
$objHumidity->getInputValue(40),
$objDateInput->getHolidaysInWeek()
)
->output(
$objIcecream->getOutputValue(90)
)
->input(
$objTemperature->getInputValue(32),
$objHumidity->getInputValue(30),
$objDateInput->getHolidaysInWeek()
)
->output(
$objIcecream->getOutputValue(70)
)
->input(
$objTemperature->getInputValue(33),
$objHumidity->getInputValue(20),
$objDateInput->getHolidaysInWeek()
)
->output(
$objIcecream->getOutputValue(75)
);
$objValues->saveToFile('values_icecreams.dat');
unset($objValues);
unset($objTemperature);
unset($objHumidity);
unset($objIcecream);
}
try
{
$objTemperature = ANN_InputValue::loadFromFile('input_temperature.dat'); // Temperature in Celsius
$objHumidity = ANN_InputValue::loadFromFile('input_humidity.dat'); // Humidity percentage
$objIcecream = ANN_OutputValue::loadFromFile('output_quantity.dat'); // Quantity of sold ice-creams
}
catch(Exception $e)
{
die('Error loading value objects');
}
try
{
$objValues = ANN_Values::loadFromFile('values_icecreams.dat');
}
catch(Exception $e)
{
die('Loading of values failed');
}
$objNetwork->setValues($objValues); // As of ANN 2.0.6
$boolTrained = $objNetwork->train();
print ($boolTrained)
? 'Network trained'
: 'Network not trained completely. Please re-run the script';
$objNetwork->saveToFile('icecreams.dat');
$objNetwork->printNetwork();