private void InitializeDataAndNeurons()
{
NormalizeData(csvPath, csvPathNormalized);
NormalizeData(csvPathTest, csvPathNormalizedTest);
Network = new SimpleNeuralNetwork((double)learningRate, (double)momentumRate, bias);
if (isRegression == false)
{
DataPointsClassificationTraining = (new ImportDataPointSets(csvPathNormalized).DataPoints);
DataPointClassificationTest = (new ImportDataPointSets(csvPathNormalizedTest).DataPoints);
Network.TrainingSet = Network.InitializeClassificationSet(DataPointsClassificationTraining, 4);
Network.TestSet = Network.InitializeClassificationSet(DataPointClassificationTest, 4);
Network.AddLayer(2);
Network.AddLayerBunch(Layers, Neurons);
Network.AddLayer(4);
}
else
{
DataPointsRegressionTraining = (new ImportDataPointsSetsRegression(csvPathNormalized).DataPoints);
DataPointRegressionTest = (new ImportDataPointsSetsRegression(csvPathNormalizedTest).DataPoints);
Network.TrainingSet = Network.InitializeRegressionSet(DataPointsRegressionTraining);
Network.TestSet = Network.InitializeRegressionSet(DataPointRegressionTest);
Network.AddLayer(1);
Network.AddLayerBunch(Layers, Neurons);
Network.AddLayer(1);
}
}