private void CreateNetwork()
{
if (trainData == null)
{
return;
}
// create network to hold all input data
var inputCount = trainData.InputCount;
uint numNeurons = Configuration.DefaultHiddenNeurons > 0 ? Configuration.DefaultHiddenNeurons : inputCount / 2 - 1;
debug($"new network: numinputs: {inputCount} neurons: {numNeurons}");
Program.Form.AddConfiguration($"\r\nConfig hash: {XRandom.randomString()}\r\n\r\nNetwork:\r\n inputs: {inputCount} neurons: {numNeurons}");
NetworkType layer = NetworkType.SHORTCUT;
network = new Network(layer, inputCount, numNeurons, 2)
{
TrainingAlgorithm = Configuration.TrainAlgo
};
network.newNetwork = true;
network.InitWeights(trainData);
network.SetupActivation();
network.SetupScaling(trainData);
}
