Examples of cc.mallet.cluster.GreedyAgglomerativeByDensity

cc.mallet.cluster.GreedyAgglomerativeByDensity
Greedily merges Instances until convergence. New merges are scored using {@link NeighborEvaluator}. Differs from {@link GreedyAgglomerative} in that one cluster iscreated at a time. That is, nodes are added to a cluster until convergence. Then, a new cluster is created from the remaining nodes. This reduces the number of comparisons from O(n^2) to O(nlg|n|). @author "Aron Culotta" @version 1.0 @since 1.0 @see GreedyAgglomerative

    InfoGain ig = new InfoGain(trainList);
    ig.print();


//     Clusterer clusterer = new GreedyAgglomerative(training.getInstances().getPipe(),
//                                                   eval, 0.5);
    Clusterer clusterer = new GreedyAgglomerativeByDensity(training.getInstances().getPipe(),
                                                           eval, 0.5, false,
                                                           new java.util.Random(1));


    // TEST
    Clustering testing = sampleClustering(alphabet);    
    InstanceList testList = testing.getInstances();
    Clustering predictedClusters = clusterer.cluster(testList);      


    // EVALUATE
    System.err.println("\n\nEvaluating System: " + clusterer);
    ClusteringEvaluators evaluators = new ClusteringEvaluators(new ClusteringEvaluator[]{
        new BCubedEvaluator(),

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      new InfoGain(trainingInstances).printByRank(System.out);
      logger.info("pairwise training accuracy="
          + new Trial(classifier, trainingInstances).getAccuracy());
      NeighborEvaluator neval = new PairwiseEvaluator(classifier, "YES",
          new PairwiseEvaluator.Average(), true);        
      clusterer = new GreedyAgglomerativeByDensity(
          training.get(0).getInstances().getPipe(), neval, 0.5, false,
          random);
      training = null;
      trainingInstances = null;
    } else {

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