/// <inheritdoc/>
public void PostIteration()
{
_lastCheck++;
_trainingError = _train.Error;
_stripOpt = Math.Min(_stripOpt, _trainingError);
_stripTotal += _trainingError;
if (_lastCheck > _stripLength)
{
_validationError = _calc.CalculateError(_validationSet);
_testError = _calc.CalculateError(_testSet);
_eOpt = Math.Min(_validationError, _eOpt);
_gl = 100.0 * ((_validationError / _eOpt) - 1.0);
_stripEfficiency = (_stripTotal)
/ (_stripLength * _stripOpt);
//System.out.println("eff=" + this.stripEfficiency + ", gl=" + this.gl);
// setup for next time
_stripTotal = 0;
_lastCheck = 0;
// should we stop?
_stop = (_gl > _alpha) ||
(_stripEfficiency < _minEfficiency);
}
}
/// <inheritdoc />
public void Init(IMLTrain theTrain)
{
_train = theTrain;
_calc = (IMLError)_train.Method;
_stop = false;
_lastCheck = 0;
_lastValidationError = _calc.CalculateError(_validationSet);
}
/// <inheritdoc />
public void PostIteration()
{
_lastCheck++;
_trainingError = _train.Error;
if (_lastCheck > _checkFrequency || Double.IsInfinity(_lastValidationError))
{
_lastCheck = 0;
double currentValidationError = _calc.CalculateError(_validationSet);
if (currentValidationError >= _lastValidationError)
{
_stop = true;
}
_lastValidationError = currentValidationError;
}
}
/// <inheritdoc />
public void Init(IMLTrain theTrain)
{
_train = theTrain;
_calc = (IMLError) _train.Method;
_stop = false;
_lastCheck = 0;
_lastValidationError = _calc.CalculateError(_validationSet);
}