Package org.apache.mahout.utils.clustering

Examples of org.apache.mahout.utils.clustering.ClusterDumper.printClusters()

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    AbstractVectorModelDistribution modelDistribution = new DistanceMeasureClusterDistribution(new VectorWritable(prototype));
    Configuration conf = new Configuration();
    DirichletDriver.run(conf, getTestTempDirPath("testdata"), output, modelDistribution, 15, 10, 1.0, true, true, 0, true);
    // run ClusterDumper
    ClusterDumper clusterDumper = new ClusterDumper(finalClusterPath(conf, output, 10), new Path(output, "clusteredPoints"));
    clusterDumper.printClusters(termDictionary);
  }

  @Test
  public void testKmeansSVD() throws Exception {
    DistanceMeasure measure = new EuclideanDistanceMeasure();
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    CanopyDriver.run(conf, svdData, output, measure, 8, 4, false, false);
    // now run the KMeans job
    KMeansDriver.run(svdData, new Path(output, "clusters-0"), output, measure, 0.001, 10, true, false);
    // run ClusterDumper
    ClusterDumper clusterDumper = new ClusterDumper(finalClusterPath(conf, output, 10), new Path(output, "clusteredPoints"));
    clusterDumper.printClusters(termDictionary);
  }

  @Test
  public void testKmeansDSVD() throws Exception {
    DistanceMeasure measure = new EuclideanDistanceMeasure();
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    CanopyDriver.run(conf, sData.getRowPath(), output, measure, 8, 4, false, false);
    // now run the KMeans job
    KMeansDriver.run(sData.getRowPath(), new Path(output, "clusters-0"), output, measure, 0.001, 10, true, false);
    // run ClusterDumper
    ClusterDumper clusterDumper = new ClusterDumper(finalClusterPath(conf, output, 10), new Path(output, "clusteredPoints"));
    clusterDumper.printClusters(termDictionary);
  }

  @Test
  public void testKmeansDSVD2() throws Exception {
    DistanceMeasure measure = new EuclideanDistanceMeasure();
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    CanopyDriver.run(conf, sData.getRowPath(), output, measure, 8, 4, false, false);
    // now run the KMeans job
    KMeansDriver.run(sData.getRowPath(), new Path(output, "clusters-0"), output, measure, 0.001, 10, true, false);
    // run ClusterDumper
    ClusterDumper clusterDumper = new ClusterDumper(finalClusterPath(conf, output, 10), new Path(output, "clusteredPoints"));
    clusterDumper.printClusters(termDictionary);
  }
}
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    Path output = getTestTempDirPath("output");
    CanopyDriver.run(new Configuration(), getTestTempDirPath("testdata"), output, measure, 8, 4, true, false);
    // run ClusterDumper
    ClusterDumper clusterDumper = new ClusterDumper(new Path(output, "clusters-0"), new Path(output, "clusteredPoints"));
    clusterDumper.printClusters(termDictionary);
  }

  @Test
  public void testKmeans() throws Exception {
    DistanceMeasure measure = new EuclideanDistanceMeasure();
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    CanopyDriver.run(conf, getTestTempDirPath("testdata"), output, measure, 8, 4, false, false);
    // now run the KMeans job
    KMeansDriver.run(conf, getTestTempDirPath("testdata"), new Path(output, "clusters-0"), output, measure, 0.001, 10, true, false);
    // run ClusterDumper
    ClusterDumper clusterDumper = new ClusterDumper(finalClusterPath(conf, output, 10), new Path(output, "clusteredPoints"));
    clusterDumper.printClusters(termDictionary);
  }

  @Test
  public void testFuzzyKmeans() throws Exception {
    DistanceMeasure measure = new EuclideanDistanceMeasure();
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                          true,
                          0,
                          false);
    // run ClusterDumper
    ClusterDumper clusterDumper = new ClusterDumper(finalClusterPath(conf, output, 10), new Path(output, "clusteredPoints"));
    clusterDumper.printClusters(termDictionary);
  }

  @Test
  public void testMeanShift() throws Exception {
    DistanceMeasure measure = new CosineDistanceMeasure();
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    Path output = getTestTempDirPath("output");
    Configuration conf = new Configuration();
    new MeanShiftCanopyDriver().run(conf, getTestTempDirPath("testdata"), output, measure, 0.5, 0.01, 0.05, 10, false, true, false);
    // run ClusterDumper
    ClusterDumper clusterDumper = new ClusterDumper(finalClusterPath(conf, output, 10), new Path(output, "clusteredPoints"));
    clusterDumper.printClusters(termDictionary);
  }

  @Test
  public void testDirichlet() throws Exception {
    Path output = getTestTempDirPath("output");
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    AbstractVectorModelDistribution modelDistribution = new SampledNormalDistribution(new VectorWritable(prototype));
    Configuration conf = new Configuration();
    DirichletDriver.run(conf, getTestTempDirPath("testdata"), output, modelDistribution, 15, 10, 1.0, true, true, 0, false);
    // run ClusterDumper
    ClusterDumper clusterDumper = new ClusterDumper(finalClusterPath(conf, output, 10), new Path(output, "clusteredPoints"));
    clusterDumper.printClusters(termDictionary);
  }

  @Test
  public void testDirichlet2() throws Exception {
    Path output = getTestTempDirPath("output");
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    AbstractVectorModelDistribution modelDistribution = new GaussianClusterDistribution(new VectorWritable(prototype));
    Configuration conf = new Configuration();
    DirichletDriver.run(conf, getTestTempDirPath("testdata"), output, modelDistribution, 15, 10, 1.0, true, true, 0, true);
    // run ClusterDumper
    ClusterDumper clusterDumper = new ClusterDumper(finalClusterPath(conf, output, 10), new Path(output, "clusteredPoints"));
    clusterDumper.printClusters(termDictionary);
  }

  @Test
  public void testDirichlet3() throws Exception {
    Path output = getTestTempDirPath("output");
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