Density-based spatial clustering of applications with noise(DBSCAN)

A fast dbscan algorithm based on Kd-tree nearest neighbor search

Invoking way:

double eps = 0.02; // radius of searching
int minPts = 1; // minimus points number
Dbscan<Clusterable> dbscan = new Dbscan<Clusterable>(eps, minPts);
List<Clusterable> instances = new LinkedList<Clusterable>();

instances.add(new Instance(new double[] {120.1, 30.2}, new Object[] {1,2,3}));
instances.add(new Instance(new double[] {120.1, 30.2}, new Object[] {4,5,6}));
	
List<Cluster<Clusterable>> clusters = dbscan.cluster(instances);
int clusterId = 0;
for (Cluster<Clusterable> cluster : clusters) {
	System.out.println(clusterId++);
	for (Clusterable instance : cluster.getInstances()) {
		System.out.println(instance);
	}
}