/// <summary>
/// Run the example.
/// </summary>
public void Process()
{
// read the iris data from the resources
Assembly assembly = Assembly.GetExecutingAssembly();
var res = assembly.GetManifestResourceStream("AIFH_Vol1.Resources.iris.csv");
// did we fail to read the resouce
if (res == null)
{
Console.WriteLine("Can't read iris data from embedded resources.");
return;
}
// load the data
var istream = new StreamReader(res);
DataSet ds = DataSet.Load(istream);
istream.Close();
// The following ranges are setup for the Iris data set. If you wish to normalize other files you will
// need to modify the below function calls other files.
ds.NormalizeRange(0, 0, 1);
ds.NormalizeRange(1, 0, 1);
ds.NormalizeRange(2, 0, 1);
ds.NormalizeRange(3, 0, 1);
IDictionary<String, int> species = ds.EncodeOneOfN(4);
IList<BasicData> trainingData = ds.ExtractSupervised(0, 4, 4, 3);
var network = new RBFNetwork(4, 4, 2);
network.Reset(new MersenneTwisterGenerateRandom());
IScoreFunction score = new ScoreRegressionData(trainingData);
var train = new TrainAnneal(network, score);
PerformIterations(train, 100000, 0.01, true);
QueryOneOfN(network, trainingData, species);
}
public void TestResetCompute()
{
var network = new RBFNetwork(2, 1, 1);
double total = network.LongTermMemory.Sum();
Assert.AreEqual(0, total, AIFH.DefaultPrecision);
network.Reset(new BasicGenerateRandom());
total += network.LongTermMemory.Sum();
Assert.IsTrue(Math.Abs(total) > AIFH.DefaultPrecision);
}