MLTrainFactory.PROPERTY_PARTICLES, false, 20);
CalculateScore score = new TrainingSetScore(training);
Randomizer randomizer = new NguyenWidrowRandomizer();
final MLTrain train = new NeuralPSO((BasicNetwork)method,randomizer,score,particles);
return train;
}