package org.encog.neural.networks.training;
import junit.framework.TestCase;
import org.encog.ml.MLRegression;
import org.encog.ml.data.MLDataSet;
import org.encog.ml.data.folded.FoldedDataSet;
import org.encog.ml.train.MLTrain;
import org.encog.neural.networks.BasicNetwork;
import org.encog.neural.networks.NetworkUtil;
import org.encog.neural.networks.XOR;
import org.encog.neural.networks.training.cross.CrossValidationKFold;
import org.encog.neural.networks.training.propagation.resilient.ResilientPropagation;
import org.encog.util.simple.EncogUtility;
import org.junit.Test;
public class TestFolded extends TestCase {
@Test
public void testRPROP() throws Throwable
{
MLDataSet trainingData = XOR.createNoisyXORDataSet(10);
BasicNetwork network = NetworkUtil.createXORNetworkUntrained();
final FoldedDataSet folded = new FoldedDataSet(trainingData);
final MLTrain train = new ResilientPropagation(network, folded);
final CrossValidationKFold trainFolded = new CrossValidationKFold(train,4);
EncogUtility.trainToError(trainFolded, 0.2);
XOR.verifyXOR((MLRegression)trainFolded.getMethod(), 0.2);
}
}