/// <summary>
/// Test the clustering of data in an Array
/// </summary>
private static void ClusterDataSetTestCase()
{
double[][] data = DataSample.GetDataSampleFromFile(10000, 25);
ClusterCollection clusters;
clusters = new KdKMeans().ClusterDataSet(5, data);
//This line has been commented out. Uncomment it to serialize your object(s)
KdKMeans.Serialize(clusters, @"kmeansclusters.xml");
}
/// <summary>
/// Test the Cluster Mean calculation between two data points
/// </summary>
private static void ClusterMean()
{
double [] John = new double[] {20, 170, 80};
double [] Henry = new double[] {30, 160, 120};
double[][] cluster = new double[2][];
cluster[0] = John;
cluster[1] = Henry;
double [] centroid = new KdKMeans().ClusterMean(cluster);
//((20+30)/2), ((170+160)/2), ((80+120)/2)
System.Diagnostics.Debug.WriteLine(centroid.ToString());
}
/// <summary>
/// Test the Manhattan Distance calculation between two data points
/// </summary>
private static void ManhattanDistanceTest()
{
double [] John = new double[] {20, 170, 80};
double [] Henry = new double[] {30, 160, 120};
double distance = new KdKMeans().ManhattanDistance(John, Henry);
System.Diagnostics.Debug.WriteLine(distance);
}
