Example usage for weka.clusterers DensityBasedClusterer clusterInstance

List of usage examples for weka.clusterers DensityBasedClusterer clusterInstance

Introduction

In this page you can find the example usage for weka.clusterers DensityBasedClusterer clusterInstance.

Prototype

int clusterInstance(Instance instance) throws Exception;

Source Link

Document

Classifies a given instance.

Usage

From source file:detplagiasi.EMClustering.java

EMClustering() {
    addd = ct.getAddress();/*from w  ww . j a v  a2  s .c om*/

    try {
        ClusterEvaluation eval;
        Instances data;
        String[] options;
        DensityBasedClusterer cl;

        File he = getArffFile();
        data = new Instances(new BufferedReader(new FileReader(he)));
        System.out.println("-----EM Clustering-----");
        // normal
        try (BufferedWriter out = new BufferedWriter(new FileWriter(addd + "\\output.txt", true))) {
            out.write("\r\n--> normal\r\n");
            options = new String[2];
            options[0] = "-t";
            options[1] = he.getAbsolutePath();
            out.write("\r\n" + ClusterEvaluation.evaluateClusterer(new EM(), options) + "\r\n");
            out.write("\r\n");

            // manual call
            out.write("\n--> manual\r\n");
            cl = new EM();
            out.write("\r\n");
            cl.buildClusterer(data);
            getDataUji();
            getDataTraining();
            System.out.println("jumlah kluster = " + cl.numberOfClusters());
            noClusterUji = cl.clusterInstance(dataUji.instance(0));
            totalCluster = cl.numberOfClusters();
            System.out.println("kluster = " + cl.clusterInstance(dataUji.instance(0)));
            for (int b = 0; b < dataTraining.numInstances(); b++) {
                System.out.print("file " + td.fileName[b] + " termasuk cluster ke ");
                array1[b] = td.fileName[b];
                array2[b] = cl.clusterInstance(dataTraining.instance(b));

                System.out.println(cl.clusterInstance(dataTraining.instance(b)));
                //simpan nilai instance ke dalam sebuah array int buat dikirim ke detplaggui
            }

            out.write("\r\n");

            eval = new ClusterEvaluation();
            eval.setClusterer(cl);
            eval.evaluateClusterer(new Instances(data));
            out.write("\r\n\n# of clusters: " + eval.getNumClusters());

        } catch (Exception e) {
            System.err.println(e.getMessage());
            System.out.println("error2 em cluster");
        }

    } catch (IOException ex) {
        Logger.getLogger(EMClustering.class.getName()).log(Level.SEVERE, null, ex);
        System.out.println("errorrrr null em");
    }
}