public void testFeedforwardPersist() throws Throwable {
NeuralDataSet trainingData = new BasicNeuralDataSet(XOR.XOR_INPUT, XOR.XOR_IDEAL);
BasicNetwork network = createNetwork();
Train train = new Backpropagation(network, trainingData, 0.7, 0.9);
for (int i = 0; i < 5000; i++) {
train.iteration();
network = (BasicNetwork) train.getNetwork();
}
TestCase.assertTrue("Error too high for backpropagation", train.getError() < 0.1);
TestCase.assertTrue("XOR outputs not correct", XOR.verifyXOR(network, 0.1));
EncogPersistedCollection encog = new EncogPersistedCollection();
encog.add(network);
encog.save("encogtest.xml");
EncogPersistedCollection encog2 = new EncogPersistedCollection();
encog2.load("encogtest.xml");
new File("encogtest.xml").delete();
BasicNetwork n = (BasicNetwork) encog2.getList().get(0);
TestCase.assertTrue("Error too high for load", n.calculateError(trainingData) < 0.1);
}
public void testClone() throws Throwable {
BasicNetwork source = XOR.createThreeLayerNet();
source.reset();
BasicNetwork target = (BasicNetwork) source.clone();
TestCase.assertTrue(target.equals(source));
}
