use weka to do Clustering - Java Machine Learning AI

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Description

use weka to do Clustering

Demo Code

/*/*from www  .  j  a  v  a2s  .c om*/
 *  How to use WEKA API in Java 
 *  Copyright (C) 2014 
 *  @author Dr Noureddin M. Sadawi (noureddin.sadawi@gmail.com)
 *  
 *  This program is free software: you can redistribute it and/or modify
 *  it as you wish ... 
 *  I ask you only, as a professional courtesy, to cite my name, web page 
 *  and my YouTube Channel!
 *  
 */

package weka.api;

//import required classes
import weka.clusterers.ClusterEvaluation;
import weka.clusterers.SimpleKMeans;
import weka.core.Instances;
import weka.core.converters.ConverterUtils.DataSource;

public class Clustering {
    public static void main(String args[]) throws Exception {
        //load dataset
        String dataset = "/home/likewise-open/ACADEMIC/csstnns/Desktop/weather.nominal.arff";
        DataSource source = new DataSource(dataset);
        //get instances object 
        Instances data = source.getDataSet();
        // new instance of clusterer
        SimpleKMeans model = new SimpleKMeans();//Simple EM (expectation maximisation)
        //number of clusters
        model.setNumClusters(4);
        //set distance function
        //model.setDistanceFunction(new weka.core.ManhattanDistance());
        // build the clusterer
        model.buildClusterer(data);
        System.out.println(model);

        //to cluster an instance .. returns cluster number as int
        //model.clusterInstance(instance);

        //returns an array containing the estimated membership probabilities of the test instance in each cluster (this should sum to at most 1)
        //model.distributionForInstance(instance);

        /*
        We can evaluate a clusterer with the ClusterEvaluation class
        For instance, separate train and test datasets can be used
        we can print out the number of clusters found
         */
        ClusterEvaluation clsEval = new ClusterEvaluation();
        //load dataset
        String dataset1 = "/home/likewise-open/ACADEMIC/csstnns/Desktop/weather.test.arff";
        DataSource source1 = new DataSource(dataset1);
        //get instances object 
        Instances data1 = source1.getDataSet();

        clsEval.setClusterer(model);
        clsEval.evaluateClusterer(data1);//this should be a test dataset!

        System.out.println("# of clusters: " + clsEval.getNumClusters());

    }
}

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