Example usage for weka.clusterers Clusterer distributionForInstance

Introduction

In this page you can find the example usage for weka.clusterers Clusterer distributionForInstance.

Prototype

public double[] distributionForInstance(Instance instance) throws Exception;

Source Link

Document

Predicts the cluster memberships for a given instance.

Usage

From source file:de.unidue.langtech.grading.tc.ClusteringTask.java

License:Open Source License

/**
 * Returns a mapping from cluster IDs to instance offsets
 * @return//www  .  j  a v a  2s .  com
 */
private Map<Integer, Set<Integer>> getClusterMap(Instances data, Clusterer clusterer) throws Exception {
    Map<Integer, Set<Integer>> clusterMap = new HashMap<Integer, Set<Integer>>();

    @SuppressWarnings("rawtypes")
    Enumeration instanceEnumeration = data.enumerateInstances();
    int instanceOffset = 0;
    while (instanceEnumeration.hasMoreElements()) {
        Instance instance = (Instance) instanceEnumeration.nextElement();
        double[] distribution = clusterer.distributionForInstance(instance);
        int clusterId = 0;
        for (double value : distribution) {
            if (new Double(value).intValue() == 1) {
                Set<Integer> clusterInstances;
                if (!clusterMap.containsKey(clusterId)) {
                    clusterInstances = new HashSet<Integer>();
                    clusterMap.put(clusterId, clusterInstances);
                }
                clusterInstances = clusterMap.get(clusterId);
                clusterInstances.add(instanceOffset);
                clusterMap.put(clusterId, clusterInstances);
            }
            clusterId++;
        }
        instanceOffset++;
    }

    return clusterMap;
}

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From source file:org.mcennis.graphrat.algorithm.clustering.WekaProbablisticClusterer.java

License:Open Source License

@Override

public void execute(Graph g) {
    ActorByMode mode = (ActorByMode) ActorQueryFactory.newInstance().create("ActorByMode");
    mode.buildQuery((String) parameter.get("GroundMode").get(), ".*", false);

    try {/*  w  ww  . ja  v  a 2 s.co m*/

        Clusterer clusterer = (Clusterer) ((Class) parameter.get("Clusterer").get()).newInstance();
        String[] options = ((String) parameter.get("Options").get()).split("\\s+");

        ((OptionHandler) clusterer).setOptions(options);

        Iterator<Actor> actor = AlgorithmMacros.filterActor(parameter, g, mode, null, null);
        Instances dataSet = null;
        while (actor.hasNext()) {
            Actor a = actor.next();
            Property property = a.getProperty(
                    AlgorithmMacros.getSourceID(parameter, g, (String) parameter.get("SourceProperty").get()));

            if (!property.getValue().isEmpty()) {

                Instance value = (Instance) property.getValue().get(0);

                if ((dataSet == null) && (value.dataset() != null)) {
                    FastVector attributes = new FastVector();
                    for (int i = 0; i < value.dataset().numAttributes(); ++i) {
                        attributes.addElement(value.dataset().attribute(i));
                    }
                    dataSet = new Instances("Clustering", attributes, 1000);
                } else if ((dataSet == null)) {
                    FastVector attributes = new FastVector();
                    for (int i = 0; i < value.numAttributes(); ++i) {
                        Attribute element = new Attribute(Integer.toString(i));
                        attributes.addElement(element);
                    }
                    dataSet = new Instances("Clustering", attributes, 1000);
                }
                dataSet.add(value);
            }

        }
        clusterer.buildClusterer(dataSet);
        actor = AlgorithmMacros.filterActor(parameter, g, mode, null, null);
        HashMap<Integer, Graph> clusters = new HashMap<Integer, Graph>();
        while (actor.hasNext()) {
            Actor a = actor.next();
            Property property = a.getProperty(
                    AlgorithmMacros.getSourceID(parameter, g, (String) parameter.get("SourceProperty").get()));
            if (!property.getValue().isEmpty()) {

                Instance instance = (Instance) property.getValue().get(0);
                double[] cluster = new double[] {};

                try {

                    cluster = clusterer.distributionForInstance(instance);
                } catch (Exception ex) {

                    Logger.getLogger(WekaClassifierClusterer.class.getName()).log(Level.SEVERE,
                            "ClusterInstance on clusterer failed", ex);

                }

                Property clusterProperty = PropertyFactory.newInstance().create("BasicProperty",
                        AlgorithmMacros.getDestID(parameter, g,
                                (String) parameter.get("DestinationProperty").get()),
                        (new double[] {}).getClass());

                clusterProperty.add(cluster);

                a.add(clusterProperty);

            }
        }

    } catch (InstantiationException ex) {

        Logger.getLogger(WekaClassifierClusterer.class.getName()).log(Level.SEVERE, null, ex);

    } catch (IllegalAccessException ex) {

        Logger.getLogger(WekaClassifierClusterer.class.getName()).log(Level.SEVERE, null, ex);

    } catch (Exception ex) {

        Logger.getLogger(WekaClassifierClusterer.class.getName()).log(Level.SEVERE, null, ex);

    }

}

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