[Java-ML-support] How to use a custom distance measure for K-medoids clustering ??

[Khirod K. N. <khi...@gm...>]

I have to use the K-medoids clustering for my project and I am having
trouble using a simple implementation. So far I have done this

import net.sf.javaml.core.*;
import net.sf.javaml.clustering.*;
import net.sf.javaml.distance.*;

public class ClusteringTest {
    public static void main(String args[]) {
        Dataset data = new DefaultDataset();

        double[] val = {1, 2, 7};
        double[] gval = {1, 2, 3};

        CustomDist de = new CustomDist();

        for (int i = 0; i < val.length; i++) {
            Instance instance = new SparseInstance(2);
            instance.put(1, val[i]);
            instance.put(2, gval[i]);

            data.add(instance);
        }


        // Test Clustering
        Clusterer km = new KMedoids(3, 10, de);
        Dataset[] clusters = km.cluster(data);

        System.out.println(clusters[0]);
        System.out.println(clusters[1]);
    }
}

class CustomDist implements DistanceMeasure {
    public boolean compare(double x, double y) {
        return x < y;
    }

    public double getMaxValue() {
        return Math.sqrt(40);
    }

    public double getMinValue() {
        return Math.sqrt(2);
    }

    public double measure(Instance x, Instance y) {
        // Use Euclidean Distance (for test only)
        double x1 = Math.abs(x.value(1) - y.value(1)) * Math.abs(x.value(1)
- y.value(1));
        double y1 = Math.abs(x.value(2) - y.value(2)) * Math.abs(x.value(2)
- y.value(2));

        return Math.sqrt(x1 + y1);
    }
}

Is there something wrong with my ClusteringTest Class??