public static void Demo()
{
PCANetwork network = PCANetwork.Create(64, 8);
var dataSet = DataGenerator.GenerateDataSet1();
var pca = new PCA(network, 0.7);
PCATrainer trainer = new PCATrainer(network, 50, pca, 0.00000005);
Normalizer3 normalizer = new Normalizer3();
//Normalizer normalizer = new Normalizer();
normalizer.Fit(dataSet.XList);
var normalizedX = normalizer.Normalize(dataSet.XList);
Utils.DisplayListList(dataSet.XList);
Console.WriteLine("--------------------------");
Utils.DisplayListList(normalizedX);
//Utils.DisplayListList(normalizer.DeNormalize(normalizedX));
trainer.Fit(normalizedX);
List <List <double> > convertedX = trainer.GetConvertedDim(normalizedX);
//convertedX=normalizer.DeNormalize(convertedX);
BPNetwork bpNetwork = BPNetwork.Create(8, new int[] { 4 /*, 4, 3*/ }, 3, ActivationFunction.SIGMOID, ActivationFunction.SIGMOID);
var bp = new BP(bpNetwork, 0.6);
BPTrainer bpTrainer = new BPTrainer(bpNetwork, 2000, bp);
bpTrainer.Fit(convertedX, dataSet.YList);
List <List <double> > predicted_ys = bpTrainer.Predict(convertedX);
CorrectCalculator correctCalculator = new CorrectCalculator();
var convertedPredictValue = NeuronOutputConverter.OrderInteger(predicted_ys);
double correct = correctCalculator.Calculate(convertedPredictValue, dataSet.YList);
Console.WriteLine("Score: {0}%", correct * 100);
}
public static void Demo()
{
PCANetwork network = PCANetwork.Create(2, 1);
var dataSet = DataGenerator.GenerateDataSet2();
var pca = new PCA(network, 0.7);
PCATrainer trainer = new PCATrainer(network, 50, pca, 0.0000005);
Normalizer2 normalizer = new Normalizer2();
normalizer.Fit(dataSet.XList);
var normalizedX = normalizer.Normalize(dataSet.XList);
trainer.Fit(normalizedX);
List <List <double> > convertedX = trainer.GetConvertedDim(normalizedX);
List <List <double> > denormalX = normalizer.DeNormalize(convertedX);
network.Display();
Console.WriteLine("OLD VECTORS===>");
Utils.DisplayListList(dataSet.XList);
Console.WriteLine("OLD VECTORS(NORMALIZED)===>");
Utils.DisplayListList(normalizedX);
Console.WriteLine("NEW VECTORS(NORMALIZED)===>");
Utils.DisplayListList(convertedX);
Console.WriteLine("NEW VECTORS===>");
Utils.DisplayListList(denormalX);
}