Exemplo n.º 1
0
        public void CreateBackPropagationTrainingAlgorithm(AnnBuild annComp, BackPropagation prop)
        {
            errorTarget = annComp.ErrorTarget;
            network.InstantiateBackPropagationAlgorithm(
                errorTarget, annComp.MaxEpochs, prop.LearningRate, prop.Beta);

            network.BuildStatsListener();
        }
Exemplo n.º 2
0
        public void TestMlpTrainingWthResilientPropPerformance()
        {
            using (wr = new StreamWriter(@"test.log", true, System.Text.Encoding.ASCII, 1024))
            {
                try
                {
                    // Build network model
                    uint[] hlayers = new uint[1];
                    hlayers[0] = 4;

                    Build(3, 1, hlayers, 1);

                    wr.WriteLine("-> Test network performance for parity problem with rprop");

                    double targetError = 0.05;
                    uint   epochs      = 10000;

                    mlpNetwork.InstantiateResilientPropagationAlgorithm(targetError, epochs);
                    mlpNetwork.BuildStatsListener();

                    Task <bool> trainResult = mlpNetwork.TrainingAsync(parityInput, parityOutput, targetError);
                    DateTime    start       = DateTime.Now;

                    while (!trainResult.IsCompleted)
                    {
                        List <double[][]> output = mlpNetwork.GetOutputValues();
                        //wr.WriteLine("[" + (DateTime.Now-start).Milliseconds.ToString() + " ms] Output {0}", string.Join(";", output));
                        Thread.Sleep(2);
                    }

                    if (!trainResult.Result)
                    {
                        wr.WriteLine("-> Network training fail");
                    }
                    else
                    {
                        wr.WriteLine("-> Network trained! [Error: {0}, Epochs: {1}]", mlpNetwork.CurrentError, mlpNetwork.EpochsTraining);
                        wr.WriteLine("-> Validation:");

                        int i = 0;
                        foreach (double[] pattern in parityInputValidation)
                        {
                            double[] output = mlpNetwork.Exec(pattern);
                            wr.WriteLine("-> Input: " + pattern[0] + " " + pattern[1]);
                            wr.WriteLine("-> Output: " + output[0] + " (ideal: " + parityOutput[i++][0] + ")");
                        }
                        wr.WriteLine("-> Validation end");
                    }
                } catch (Exception e)
                {
                    wr.WriteLine(e.Message + Environment.NewLine + e.StackTrace);
                }
            }
        }