private static void MNISTTrainNetwork(FeedforwardNeuralNetwork fnn, TrainingExample[] trainingExamples, TrainingExample[] testExamples) { Console.WriteLine("\nBeginning neural network training procedure.\n"); Console.WriteLine("Enter desired number of epochs."); string epochsStr = Console.ReadLine(); int epochs = Convert.ToInt32(epochsStr); do { Console.WriteLine("Please wait for training cycle to complete..."); var timer = Stopwatch.StartNew(); fnn.TrainEpochs(trainingExamples, epochs); Console.WriteLine("Training cycle completed in " + timer.Elapsed + "."); Console.WriteLine("Test network? Enter Y for yes or anything else for no."); string inputStr = Console.ReadLine(); char input = Convert.ToChar(inputStr); if (input == 'Y') { MNISTTestNetwork(fnn, testExamples); } Console.WriteLine("Continue training? Enter 0 for no or a valid number of epochs for yes."); epochsStr = Console.ReadLine(); epochs = Convert.ToInt32(epochsStr); } while (epochs > 0); }
public static void DecimalBinaryExample() { int[] layers = new int[] { 2, 5, 4 }; FeedforwardNeuralNetwork fnn = new FeedforwardNeuralNetwork(layers, 1.0F, 0.1F); DecimalBinaryTestNetwork(fnn); Matrix[] expectedOutputs = { new Matrix(new float[4, 1] { { 1 }, { 0 }, { 0 }, { 0 } }), new Matrix(new float[4, 1] { { 0 }, { 1 }, { 0 }, { 0 } }), new Matrix(new float[4, 1] { { 0 }, { 0 }, { 1 }, { 0 } }), new Matrix(new float[4, 1] { { 0 }, { 0 }, { 0 }, { 1 } }) }; Matrix[] inputs = { new Matrix(new float[2, 1] { { 0 }, { 0 } }), new Matrix(new float[2, 1] { { 0 }, { 1 } }), new Matrix(new float[2, 1] { { 1 }, { 0 } }), new Matrix(new float[2, 1] { { 1 }, { 1 } }) }; TrainingExample[] examples = new TrainingExample[4]; for (int i = 0; i < 4; ++i) { examples[i] = new TrainingExample(inputs[i], expectedOutputs[i]); } fnn.TrainEpochs(examples, 1000); DecimalBinaryTestNetwork(fnn); }
public static void DecimalBinaryExample() { int[] layers = new int[] { 2, 5, 4 }; FeedforwardNeuralNetwork fnn = new FeedforwardNeuralNetwork(layers, 1.0F, 0.1F); DecimalBinaryTestNetwork(fnn); Matrix[] expectedOutputs = { new Matrix(new float[4,1]{ {1}, {0}, {0}, {0}}), new Matrix(new float[4,1]{ {0}, {1}, {0}, {0}}), new Matrix(new float[4,1]{ {0}, {0}, {1}, {0}}), new Matrix(new float[4,1]{ {0}, {0}, {0}, {1}})}; Matrix[] inputs = { new Matrix(new float[2,1]{ {0}, {0}}), new Matrix(new float[2,1]{ {0}, {1}}), new Matrix(new float[2,1]{ {1}, {0}}), new Matrix(new float[2,1]{ {1}, {1}})}; TrainingExample[] examples = new TrainingExample[4]; for (int i = 0; i < 4; ++i) { examples[i] = new TrainingExample(inputs[i], expectedOutputs[i]); } fnn.TrainEpochs(examples, 1000); DecimalBinaryTestNetwork(fnn); }
private static void MNISTTrainNetwork(FeedforwardNeuralNetwork fnn, TrainingExample[] trainingExamples, TrainingExample[] testExamples) { Console.WriteLine("\nBeginning neural network training procedure.\n"); Console.WriteLine("Enter desired number of epochs."); string epochsStr = Console.ReadLine(); int epochs = Convert.ToInt32(epochsStr); do { Console.WriteLine("Please wait for training cycle to complete..."); var timer = Stopwatch.StartNew(); fnn.TrainEpochs(trainingExamples, epochs); Console.WriteLine("Training cycle completed in " + timer.Elapsed + "."); Console.WriteLine("Test network? Enter Y for yes or anything else for no."); string inputStr = Console.ReadLine(); char input = Convert.ToChar(inputStr); if (input == 'Y') { MNISTTestNetwork(fnn, testExamples); } Console.WriteLine("Continue training? Enter 0 for no or a valid number of epochs for yes."); epochsStr = Console.ReadLine(); epochs = Convert.ToInt32(epochsStr); } while (epochs > 0); }