static void Main(string[] args)
{
Console.WriteLine("--------------------------------------");
Console.WriteLine(" Data Mining Assignment 3 ");
Console.WriteLine(" K-Means Algorithm implementation ");
Console.WriteLine(" by Volkan Paksoy ");
Console.WriteLine("--------------------------------------");
///////////////////////////////////////////////////////////////
// Get required parameters from the user: Number of clusters (k)
// and the path for the database file
Console.Write("Enter the number of clusters: ");
string strK = Console.ReadLine();
int k = -1;
bool bKEntered = Int32.TryParse(strK, out k);
if (!bKEntered || k < 0)
{
Console.WriteLine("Invalid k value");
return;
}
Console.Write("Enter path for database : ");
filePath = Console.ReadLine();
if (!File.Exists(filePath))
{
Console.WriteLine("File does not exist");
return;
}
///////////////////////////////////////////////////////////////
KMeansAlgorithm kmeans = new KMeansAlgorithm();
kmeans.K = k;
kmeans.FilePath = filePath;
kmeans.Run();
Console.WriteLine("K-Means clustering completed.");
Console.WriteLine();
Console.WriteLine("Clustering output : ");
Console.WriteLine("----------------------");
Console.WriteLine(kmeans.GetOutput());
Console.ReadLine();
}
private void btnRunKMeans1_Click(object sender, EventArgs e)
{
string filePath = txtFilePath.Text;
Dictionary<int, ClusterObject> m_lstData = DataLoader.LoadData(filePath);
KMeansAlgorithm kmeans = new KMeansAlgorithm();
kmeans.K = Int32.Parse(txtClusterCount.Text);
kmeans.FilePath = filePath;
kmeans.Run();
using (Graphics g = pnlGraph.CreateGraphics())
using (CPI.Plot3D.Plotter3D p = new CPI.Plot3D.Plotter3D(g))
{
g.Clear(this.BackColor);
foreach (KeyValuePair<int, ClusterObject> kvp in kmeans.ClusteredData)
{
p.Location = new CPI.Plot3D.Point3D((int)kvp.Value.Coordinates[0], (int)kvp.Value.Coordinates[1], 0);
DrawSquare(p, 1, kvp.Value.ClusterId);
}
}
}
