generate cluster

public void example() throws NumberFormatException, IOException, ClassNotFoundException, OperatorException
{
	BufferedReader input = new BufferedReader(new FileReader("patternss.csv"));

	while ((line = input.readLine()) != null)
	{
		split = line.split(",");
		pattern = split[0];
		supp = new double[4];

		for (int i = 1; i < split.length; i++ )
		{
			supp[i-1] = Double.parseDouble(split);
		}

		mapPattern.put(pattern, supp);
	}

	int j=0;

	attributes = new LinkedList<Attribute>();

	for (String namePattern : mapPattern.keySet())
	{

		for ( int a = 1; a < split.length; a++) 
		{

			attributes.add(AttributeFactory.createAttribute ("supp["+j+"]" + " : " + mapPattern.get(namePattern)[a-1], Ontology.REAL));
			j++;
		}
	}
	label = AttributeFactory.createAttribute ("label", Ontology.NOMINAL);

	attributes.add(label);

	// create table
	MemoryExampleTable table = new MemoryExampleTable(attributes);

	for (int i=1; i<split.length; i++) 
	{

		for (String namePattern : mapPattern.keySet()) 
		{
			data = new double[attributes.size()];
			for ( int a = 1; a < attributes.size(); a++)
			{
				// fill with proper data here
				data = mapPattern.get(namePattern)[i-1];

			}
			// maps the nominal classification to a double value
			data[data.length - 1] = label.getMapping().mapString(namePattern);		

		// add data row
		table.addDataRow(new DoubleArrayDataRow(data));
		}
	}

	// create example set
	ExampleSet exampleSet = table.createExampleSet(label);

	exampleSet.getAttributes().setId(label);
	System.out.println(exampleSet.getAttributes().getId());
	System.out.println(exampleSet.getAttributes());
	OperatorDescription opDesc = new OperatorDescription(CreatingExampleTables.class.getClassLoader(), "Cluster", CreatingExampleTables.class.getName(), "Clustering with DBScan", null, "gruppi", null, null);


	DBScan scan = new DBScan(opDesc);
	scan.setParameter("min_points", Double.toString(5));
scan.setParameter("epsilon", Double.toString(0.1));
	ClusterModel cluster = scan.generateClusterModel(exampleSet);

	System.out.println(cluster.getClusters());

	}