public static weka.clusterers.Clusterer CreateCluster()
{
weka.clusterers.RandomizableClusterer cluster = new weka.clusterers.SimpleKMeans();
cluster.setOptions(weka.core.Utils.splitOptions("-V -M -N 10 -A \"weka.core.EuclideanDistance -R first-last\" -I 500 -O -S 10"));
return(cluster);
}
public void TestCluster()
{
//string modelFileName = string.Format("{0}\\cluster.model", m_baseDir);
//var cluster = (weka.clusterers.SimpleKMeans)weka.core.SerializationHelper.read(modelFileName);
weka.clusterers.SimpleKMeans cluster = new weka.clusterers.SimpleKMeans();
Instances origInstances = WekaUtils.LoadInstances(GetArffFileName(true, "B", "new"));
Instances noClassInstances = WekaUtils.RemoveClassAttribute(origInstances);
//foreach (Instance i in origInstances)
//{
// List<double> d = new List<double>();
// foreach (Instance j in cluster.getClusterCentroids())
// {
// d.Add(cluster.getDistanceFunction().distance(i, j));
// }
//}
for (int c = 5; c <= 200; ++c)
{
cluster.setOptions(weka.core.Utils.splitOptions(string.Format("-V -M -N {0} -A \"weka.core.EuclideanDistance -R first-last\" -I 500 -O -S 10", c)));
cluster.buildClusterer(noClassInstances);
double d = cluster.getSquaredError();
WekaUtils.Instance.WriteLog(string.Format("{0}: {1}", c, d));
}
}