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(); } }