Example usage for weka.clusterers HierarchicalClusterer distributionForInstance

Introduction

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

Prototype

@Override
    
    public double[] distributionForInstance(Instance instance) throws Exception 

Source Link

Usage

From source file:eu.cassandra.server.mongo.csn.MongoCluster.java

License:Apache License

public DBObject clusterHierarchical(String message, String graph_id, String run_id, String clusterBasedOn,
        int numberOfClusters, String name, String clusterbasedon) {
    try {/*from   ww w.j  a v  a 2 s. c  o  m*/
        Instances instances = getInstances(clusterBasedOn, graph_id);
        if (instances.numInstances() < 2) {
            return new JSONtoReturn().createJSONError(message, new Exception("Number of CSN Nodes is < 2"));
        }

        HierarchicalClusterer h = new HierarchicalClusterer();
        h.setOptions(new String[] { "-L", "AVERAGE" });
        h.setDistanceFunction(new EuclideanDistance());
        if (numberOfClusters > 0)
            h.setNumClusters(numberOfClusters);
        h.buildClusterer(instances);

        HashMap<Integer, Vector<String>> clusters = new HashMap<Integer, Vector<String>>();
        double[] arr;
        for (int i = 0; i < instances.numInstances(); i++) {
            String nodeId = nodeIDs.get(i);
            arr = h.distributionForInstance(instances.instance(i));
            for (int j = 0; j < arr.length; j++) {
                if (arr[j] == 1.0) {
                    if (!clusters.containsKey(j)) {
                        Vector<String> nodes = new Vector<String>();
                        nodes.add(nodeId);
                        clusters.put(j, nodes);
                    } else {
                        Vector<String> nodes = clusters.get(j);
                        nodes.add(nodeId);
                        clusters.put(j, nodes);
                    }
                }
            }
        }
        return saveClusters(graph_id, run_id, "hierarchical", clusters, null, name, clusterbasedon);
    } catch (Exception e) {
        e.printStackTrace();
        return new JSONtoReturn().createJSONError(message, e);
    }
}

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From source file:org.iobserve.analysis.behavior.clustering.hierarchical.ClusteringResultsBuilder.java

License:Apache License

/**
 * Build clustering result list of clustered instances and their assigned clusters.
 *
 * @param instances//from w w w .j  av  a  2s  . c  o  m
 *            Input data that is clustered.
 *
 * @param hierarchicalClusterer
 *            Weka-clusterer that performs the hierarchical clustering.
 *
 * @return clusteringResults
 */
public static Map<Integer, List<Pair<Instance, Double>>> buildClusteringResults(final Instances instances,
        final HierarchicalClusterer hierarchicalClusterer) {
    /*
     * An entry of the map looks like this: <clusterID, <instance, 1.0>>. The 1,0 is the
     * probability that the instance is in this cluster. It is needed for unity of clustering
     * output data.
     */
    final Map<Integer, List<Pair<Instance, Double>>> clusteringResults = new HashMap<>(); // NOPMD;

    for (int i = 0; i < instances.numInstances(); i++) {
        final Instance currentInstance = instances.instance(i);
        try {
            final int cluster = hierarchicalClusterer.clusterInstance(currentInstance);
            final double probability = hierarchicalClusterer.distributionForInstance(currentInstance)[cluster];
            if (clusteringResults.get(cluster) == null) {
                clusteringResults.put(cluster, new LinkedList<Pair<Instance, Double>>());
            }
            clusteringResults.get(cluster).add(new Pair<>(currentInstance, probability));
        } catch (final Exception e) { // NOPMD NOCS api dependency
            ClusteringResultsBuilder.LOGGER.error("Failed building hierarchical clustering.", e);
        }

    }

    return clusteringResults;
}

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