Package org.apache.mahout.common.distance

Examples of org.apache.mahout.common.distance.DistanceMeasure

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    plotSampleData((Graphics2D) g);
    plotClusters((Graphics2D) g);
  }

  public static void main(String[] args) throws Exception {
    DistanceMeasure measure = new ManhattanDistanceMeasure();

    Path samples = new Path("samples");
    Path output = new Path("output");
    HadoopUtil.overwriteOutput(samples);
    HadoopUtil.overwriteOutput(output);
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    initialize();
    this.setTitle("k-Means Clusters (>" + (int) (significance * 100) + "% of population)");
  }

  public static void main(String[] args) throws Exception {
    DistanceMeasure measure = new ManhattanDistanceMeasure();
    Path samples = new Path("samples");
    Path output = new Path("output");
    HadoopUtil.overwriteOutput(samples);
    HadoopUtil.overwriteOutput(output);

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          .parseInt(getOption(DefaultOptionCreator.CLUSTER_FILTER_OPTION));
    }
    boolean runClustering = hasOption(DefaultOptionCreator.CLUSTERING_OPTION);
    boolean runSequential = getOption(DefaultOptionCreator.METHOD_OPTION)
        .equalsIgnoreCase(DefaultOptionCreator.SEQUENTIAL_METHOD);
    DistanceMeasure measure = ClassUtils.instantiateAs(measureClass, DistanceMeasure.class);
    run(conf, input, output, measure, t1, t2, t3, t4, clusterFilter,
        runClustering, runSequential);
    return 0;
  }
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      }

      // run mapper
      FuzzyKMeansMapper mapper = new FuzzyKMeansMapper();
      mapper.config(clusterList);
      DistanceMeasure measure = new EuclideanDistanceMeasure();
      Configuration conf = new Configuration();
      conf.set(FuzzyKMeansConfigKeys.DISTANCE_MEASURE_KEY, measure.getClass().getName());
      conf.set(FuzzyKMeansConfigKeys.CLUSTER_CONVERGENCE_KEY, "0.001");
      conf.set(FuzzyKMeansConfigKeys.M_KEY, "2");
      conf.set(FuzzyKMeansConfigKeys.EMIT_MOST_LIKELY_KEY, "true");
      conf.set(FuzzyKMeansConfigKeys.THRESHOLD_KEY, "0");
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      }

      // run mapper
      FuzzyKMeansMapper mapper = new FuzzyKMeansMapper();
      mapper.config(clusterList);
      DistanceMeasure measure = new EuclideanDistanceMeasure();
      Configuration conf = new Configuration();
      conf.set(FuzzyKMeansConfigKeys.DISTANCE_MEASURE_KEY, measure.getClass().getName());
      conf.set(FuzzyKMeansConfigKeys.CLUSTER_CONVERGENCE_KEY, "0.001");
      conf.set(FuzzyKMeansConfigKeys.M_KEY, "2");
      conf.set(FuzzyKMeansConfigKeys.EMIT_MOST_LIKELY_KEY, "true");
      conf.set(FuzzyKMeansConfigKeys.THRESHOLD_KEY, "0");
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      }

      // run mapper
      FuzzyKMeansMapper mapper = new FuzzyKMeansMapper();
      mapper.config(clusterList);
      DistanceMeasure measure = new EuclideanDistanceMeasure();

      Configuration conf = new Configuration();
      conf.set(FuzzyKMeansConfigKeys.DISTANCE_MEASURE_KEY, measure.getClass().getName());
      conf.set(FuzzyKMeansConfigKeys.CLUSTER_CONVERGENCE_KEY, "0.001");
      conf.set(FuzzyKMeansConfigKeys.M_KEY, "2");
      conf.set(FuzzyKMeansConfigKeys.EMIT_MOST_LIKELY_KEY, "true");
      conf.set(FuzzyKMeansConfigKeys.THRESHOLD_KEY, "0");
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    double convergenceDelta = Double.parseDouble(getOption(DefaultOptionCreator.CONVERGENCE_DELTA_OPTION));
    int maxIterations = Integer.parseInt(getOption(DefaultOptionCreator.MAX_ITERATIONS_OPTION));
    if (hasOption(DefaultOptionCreator.OVERWRITE_OPTION)) {
      HadoopUtil.delete(getConf(), output);
    }
    DistanceMeasure measure = ClassUtils.instantiateAs(measureClass, DistanceMeasure.class);

    if (hasOption(DefaultOptionCreator.NUM_CLUSTERS_OPTION)) {
      clusters = RandomSeedGenerator.buildRandom(getConf(), input, clusters, Integer
          .parseInt(getOption(DefaultOptionCreator.NUM_CLUSTERS_OPTION)), measure);
    }
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  @Override
  protected void setup(Context context) throws IOException, InterruptedException {
    super.setup(context);
    Configuration conf = context.getConfiguration();
    DistanceMeasure measure =
        ClassUtils.instantiateAs(conf.get(KMeansConfigKeys.DISTANCE_MEASURE_KEY), DistanceMeasure.class);
    measure.configure(conf);

    this.clusterer = new KMeansClusterer(measure);

    String clusterPath = conf.get(KMeansConfigKeys.CLUSTER_PATH_KEY);
    if (clusterPath != null && !clusterPath.isEmpty()) {
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  @Override
  protected void setup(Context context) throws IOException, InterruptedException {
    super.setup(context);
    Configuration conf = context.getConfiguration();
    DistanceMeasure measure =
        ClassUtils.instantiateAs(conf.get(KMeansConfigKeys.DISTANCE_MEASURE_KEY), DistanceMeasure.class);
    measure.configure(conf);

    String clusterPath = conf.get(KMeansConfigKeys.CLUSTER_PATH_KEY);
    if (clusterPath != null && !clusterPath.isEmpty()) {
      KMeansUtil.configureWithClusterInfo(conf, new Path(clusterPath), clusters);
      if (clusters.isEmpty()) {
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  @Override
  protected void setup(Context context) throws IOException, InterruptedException {
    super.setup(context);
    Configuration conf = context.getConfiguration();
    DistanceMeasure measure =
        ClassUtils.instantiateAs(conf.get(KMeansConfigKeys.DISTANCE_MEASURE_KEY), DistanceMeasure.class);
    measure.configure(conf);

    this.convergenceDelta = Double.parseDouble(conf.get(KMeansConfigKeys.CLUSTER_CONVERGENCE_KEY));
    this.clusterer = new KMeansClusterer(measure);
    this.clusterMap = Maps.newHashMap();
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Related Classes of org.apache.mahout.common.distance.DistanceMeasure

  • mia.clustering.ch10.InterClusterDistances
  • org.apache.mahout.clustering.canopy.CanopyConfigKeys
  • org.apache.mahout.clustering.canopy.CanopyDriver
  • org.apache.mahout.clustering.cdbw.TestCDbwEvaluator
  • org.apache.mahout.clustering.classify.ClusterClassificationDriver
  • org.apache.mahout.clustering.classify.ClusterClassificationMapper
  • org.apache.mahout.clustering.ClusteringUtils
  • org.apache.mahout.clustering.dirichlet.DirichletDriver
  • org.apache.mahout.clustering.dirichlet.models.DistributionDescription
  • org.apache.mahout.clustering.display.DisplayFuzzyKMeans
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