static void Main()
{
Console.WriteLine("\nBegin Build 2013 neural network demo");
Console.WriteLine("\nData is the famous Iris flower set.");
Console.WriteLine("Data is sepal length, sepal width, petal length, petal width -> iris species");
Console.WriteLine("Iris setosa = 0 0 1, Iris versicolor = 0 1 0, Iris virginica = 1 0 0 ");
Console.WriteLine("The goal is to predict species from sepal length, width, petal length, width\n");
Console.WriteLine("Raw data resembles:\n");
Console.WriteLine(" 5.1, 3.5, 1.4, 0.2, Iris setosa");
Console.WriteLine(" 7.0, 3.2, 4.7, 1.4, Iris versicolor");
Console.WriteLine(" 6.3, 3.3, 6.0, 2.5, Iris virginica");
Console.WriteLine(" ......\n");
var allData = new TrainingData();
allData.LoadData("irisdata.txt", 4, 3);
var sb = new StringBuilder();
ArrayFormatter.Matrix(sb, allData.Data, 6, 1, true, "\nFirst 6 rows of entire 150-item data set:");
Console.WriteLine(sb.ToString());
Console.WriteLine("Creating 80% training and 20% test data matrices");
allData.Split(0.8);
sb.Clear();
ArrayFormatter.Matrix(sb, allData.TrainData, 5, 1, true, "\nFirst 5 rows of training data:");
Console.WriteLine(sb.ToString());
sb.Clear();
ArrayFormatter.Matrix(sb, allData.TestData, 3, 1, true, "\nFirst 3 rows of test data:");
Console.WriteLine(sb.ToString());
allData.NormalizeInputs();
sb.Clear();
ArrayFormatter.Matrix(sb, allData.TrainData, 5, 1, true, "\nFirst 5 rows of normalized training data:");
Console.WriteLine(sb.ToString());
sb.Clear();
ArrayFormatter.Matrix(sb, allData.TestData, 3, 1, true, "First 3 rows of normalized test data:");
Console.Write(sb.ToString());
Console.WriteLine("\nBuilding Neural Networks");
Console.WriteLine("Hard-coded tanh function for input-to-hidden and softmax for hidden-to-output activations");
var networks = new List <INeuralNetwork> {
BuildBackPropNetwork(), BuildPsoNetwork()
};
foreach (var network in networks)
{
Console.WriteLine("\n\nTraining Network: " + network.GetType());
var sw = new Stopwatch();
sw.Start();
network.Train(allData.TrainData);
var ts = sw.Elapsed;
Console.WriteLine(
"Training complete in {0}",
string.Format("{0:00}:{1:00}:{2:00}.{3:000}", ts.Hours, ts.Minutes, ts.Seconds, ts.Milliseconds));
var trainAcc = network.Accuracy(allData.TrainData);
var testAcc = network.Accuracy(allData.TestData);
Console.WriteLine("\nAccuracy on training data = " + trainAcc.ToString("F4"));
Console.WriteLine("\nAccuracy on test data = " + testAcc.ToString("F4"));
Console.WriteLine("\n\nFinal Network: {0}", network);
}
Console.WriteLine("\nEnd Build 2013 neural network demo\n");
Console.ReadLine();
}
