throws IOException, ClassNotFoundException, InterruptedException { ClusterClassifier.writePolicy(new FuzzyKMeansClusteringPolicy(m, convergenceDelta), clustersIn); ClusterClassificationDriver.run(conf, input, output, new Path(output, PathDirectory.CLUSTERED_POINTS_DIRECTORY), threshold, emitMostLikely, runSequential);
throws IOException, ClassNotFoundException, InterruptedException { ClusterClassifier.writePolicy(new FuzzyKMeansClusteringPolicy(m, convergenceDelta), clustersIn); ClusterClassificationDriver.run(conf, input, output, new Path(output, PathDirectory.CLUSTERED_POINTS_DIRECTORY), threshold, emitMostLikely, runSequential);
throws IOException, ClassNotFoundException, InterruptedException { ClusterClassifier.writePolicy(new FuzzyKMeansClusteringPolicy(m, convergenceDelta), clustersIn); ClusterClassificationDriver.run(conf, input, output, new Path(output, PathDirectory.CLUSTERED_POINTS_DIRECTORY), threshold, emitMostLikely, runSequential);
ClusteringPolicy policy = new FuzzyKMeansClusteringPolicy(m, convergenceDelta); ClusterClassifier prior = new ClusterClassifier(clusters, policy); prior.writeToSeqFiles(priorClustersPath);
ClusteringPolicy policy = new FuzzyKMeansClusteringPolicy(m, convergenceDelta); ClusterClassifier prior = new ClusterClassifier(clusters, policy); prior.writeToSeqFiles(priorClustersPath);
ClusteringPolicy policy = new FuzzyKMeansClusteringPolicy(m, convergenceDelta); ClusterClassifier prior = new ClusterClassifier(clusters, policy); prior.writeToSeqFiles(priorClustersPath);
private static ClusterClassifier newSoftClusterClassifier() { List<Cluster> models = Lists.newArrayList(); DistanceMeasure measure = new ManhattanDistanceMeasure(); models.add(new SoftCluster(new DenseVector(2).assign(1), 0, measure)); models.add(new SoftCluster(new DenseVector(2), 1, measure)); models.add(new SoftCluster(new DenseVector(2).assign(-1), 2, measure)); return new ClusterClassifier(models, new FuzzyKMeansClusteringPolicy()); }