/// <summary>
/// Perform the example.
/// </summary>
public void Run()
{
// 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();
// perform the cluster
IList<BasicData> observations = ds.ExtractUnsupervisedLabeled(4);
KMeansClustering kmeans = new KMeansClustering(3);
kmeans.InitForgy(observations);
int iterations = kmeans.Iteration(1000);
Console.WriteLine("Finished after " + iterations + " iterations.");
for (int i = 0; i < kmeans.K; i++)
{
Cluster cluster = kmeans.Clusters[i];
Console.WriteLine("* * * Cluster #" + i);
foreach (BasicData d in cluster.Observations)
{
Console.WriteLine(d.ToString());
}
}
}
public void TestClusterForgy()
{
var kmeans = new KMeansClustering(4) {RandomGeneration = new BasicGenerateRandom(22)};
kmeans.InitForgy(GetDataSet());
int iterations = kmeans.Iteration(1000);
Assert.AreEqual(2, iterations);
Cluster cluster1 = kmeans.Clusters[0];
Cluster cluster2 = kmeans.Clusters[1];
Cluster cluster3 = kmeans.Clusters[2];
Cluster cluster4 = kmeans.Clusters[3];
Assert.AreEqual(3, cluster1.Observations.Count);
Assert.AreEqual(3, cluster2.Observations.Count);
Assert.AreEqual(3, cluster3.Observations.Count);
Assert.AreEqual(3, cluster4.Observations.Count);
}
public void TestTooManyClusters()
{
var kmeans = new KMeansClustering(13);
kmeans.InitRandom(GetDataSet());
}
public void TestNoObservations()
{
IList<BasicData> list = new List<BasicData>();
var kmeans = new KMeansClustering(3);
kmeans.InitForgy(list);
}
public void TestNoDimension()
{
IList<BasicData> list = new List<BasicData>();
list.Add(new BasicData(0));
var kmeans = new KMeansClustering(3);
kmeans.InitForgy(list);
}
public void TestMaxClusters()
{
var kmeans = new KMeansClustering(12);
kmeans.RandomGeneration = new BasicGenerateRandom(22);
kmeans.InitRandom(GetDataSet());
int iterations = kmeans.Iteration(1000);
Assert.AreEqual(1, iterations);
}
public void TestGeneral()
{
var kmeans = new KMeansClustering(5);
Assert.AreEqual(5, kmeans.K);
kmeans.RandomGeneration = new BasicGenerateRandom();
kmeans.DistanceMetric = new EuclideanDistance();
}
public void TestEarlyIteration()
{
var kmeans = new KMeansClustering(3);
kmeans.Iteration();
}
