public static void InitializeSimpleNetwork(int interations)
{
NormalizeData();
List <DataPointCls> points = (new ImportDataPointSets(csvPathNormalized).DataPoints);
SimpleNeuralNetwork myNetwork = new SimpleNeuralNetwork();
//myNetwork.InitializeTrainingSet(points,4);
var ts = myNetwork.TrainingSet;
myNetwork.ActivationFunction = new ActivationBiPolar();
myNetwork.AddLayer(2);
myNetwork.AddLayerBunch(2, 4);
myNetwork.AddLayer(4);
myNetwork.StartLearning(interations);
//ErrorCalculator.CalculateError(myNetwork.ComputeTrainingSet().ToList(), myNetwork);
}
public void Run()
{
IOutput writer = MyCore.Resolve <IOutput>();
if (csvPath == null)
{
writer.Write("Please load training set first!");
return;
}
if (this.csvPathTest == null)
{
writer.Write("Please load test set first!");
return;
}
InitializeDataAndNeurons();
if (!UnipolarChecked)
{
Network.SetBiPolarActivation();
}
else
{
Network.SetSigmoidActivation();
}
Network.StartLearning(Iterations);
LearningProcess = Network.learningProcess;
DrawLearningRate();
Network.ComputeSet(Network.TestSet);
resultList = Network.resultList;
if (!isRegression)
{
DrawGraph();
}
else
{
DrawRegressionFunction();
}
}