public void CNNTest()
{
network.AddInputLayer(7, 1);
network.AddConvolutionLayer(2, 2);
network.AddPoolingLayer(2);
network.AddActivationLayer(ActivatorType.Relu);
network.AddConvolutionLayer(3, 2);
network.AddPoolingLayer(2);
network.AddActivationLayer(ActivatorType.Relu);
network.AddFlattenLayer();
network.AddDenseLayer(5, true);
network.AddActivationLayer(ActivatorType.Relu);
network.AddDenseLayer(3, false);
network.AddSoftMaxLayer();
TestNetwork(network, "test1");
}
private static Network CreateModel()
{
var network = new Network(LossFunctionType.CrossEntropy, new Flat(0.001), NumberOfClasses);
network.AddInputLayer(28, 1);
network.AddConvolutionLayer(16, 5);
network.AddActivationLayer(ActivatorType.Relu);
network.AddPoolingLayer(2);
network.AddConvolutionLayer(32, 5);
network.AddActivationLayer(ActivatorType.Relu);
network.AddPoolingLayer(2);
network.AddFlattenLayer();
network.AddDenseLayer(1024, true);
network.AddActivationLayer(ActivatorType.Relu);
network.AddDenseLayer(NumberOfClasses, false);
network.AddSoftMaxLayer();
network.RandomizeWeights(0.1);
return(network);
}