/// <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); }