/**
* Calculate the error for this neural network.
* The error is calculated
* using root-mean-square(RMS).
*
* @param
* MLDataSet data
* The training set.
* @return double The error percentage.
*/
public function calculateError(MLDataSet $data)
{
$errorCalculation = new ErrorCalculation();
$actual = array();
$pair = BasicMLDataPair::createPair($data->getInputSize(), $data->getIdealSize());
for ($i = 0; $i < $data->getRecordCount(); ++$i) {
$data->getRecord($i, $pair);
$this->compute($pair->getInputArray(), $actual);
$errorCalculation->updateError($actual, $pair->getIdealArray(), $pair->getSignificance());
}
return $errorCalculation->calculate();
}
