Package org.apache.mahout.clustering.evaluation

Examples of org.apache.mahout.clustering.evaluation.ClusterEvaluator.interClusterDensity()


    Canopy cluster = new Canopy(new DenseVector(new double[] {10, 10}), 19, measure);
    clusters.add(cluster);
    List<VectorWritable> points = Lists.newArrayList();
    representativePoints.put(cluster.getId(), points);
    ClusterEvaluator evaluator = new ClusterEvaluator(representativePoints, clusters, measure);
    assertEquals("inter cluster density", 0.371534146934532, evaluator.interClusterDensity(), EPSILON);
    assertEquals("intra cluster density", 0.3656854249492381, evaluator.intraClusterDensity(), EPSILON);
  }
 
  /**
   * adding an single-valued cluster should modify the inter cluster density but not change the intra-cluster density as
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    clusters.add(cluster);
    List<VectorWritable> points = Lists.newArrayList();
    points.add(new VectorWritable(cluster.getCenter().plus(new DenseVector(new double[] {1, 1}))));
    representativePoints.put(cluster.getId(), points);
    ClusterEvaluator evaluator = new ClusterEvaluator(representativePoints, clusters, measure);
    assertEquals("inter cluster density", 0.3656854249492381, evaluator.interClusterDensity(), EPSILON);
    assertEquals("intra cluster density", 0.3656854249492381, evaluator.intraClusterDensity(), EPSILON);
  }
 
  /**
   * Representative points extraction will duplicate the cluster center if the cluster has no assigned points. These
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    points.add(new VectorWritable(cluster.getCenter()));
    points.add(new VectorWritable(cluster.getCenter()));
    points.add(new VectorWritable(cluster.getCenter()));
    representativePoints.put(cluster.getId(), points);
    ClusterEvaluator evaluator = new ClusterEvaluator(representativePoints, clusters, measure);
    assertEquals("inter cluster density", 0.3656854249492381, evaluator.interClusterDensity(), EPSILON);
    assertEquals("intra cluster density", 0.3656854249492381, evaluator.intraClusterDensity(), EPSILON);
  }
 
  @Test
  public void testCanopy() throws Exception {
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        numIterations, true);
    //printRepPoints(numIterations);
    ClusterEvaluator evaluator = new ClusterEvaluator(conf, clustersIn);
    // now print out the Results
    System.out.println("Intra-cluster density = " + evaluator.intraClusterDensity());
    System.out.println("Inter-cluster density = " + evaluator.interClusterDensity());
  }
 
  @Test
  public void testKmeans() throws Exception {
    ClusteringTestUtils.writePointsToFile(sampleData, new Path(testdata, "file1"), fs, conf);
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        numIterations, true);
    RepresentativePointsDriver.printRepresentativePoints(kmeansOutput, numIterations);
    ClusterEvaluator evaluator = new ClusterEvaluator(conf, clustersIn);
    // now print out the Results
    System.out.println("Intra-cluster density = " + evaluator.intraClusterDensity());
    System.out.println("Inter-cluster density = " + evaluator.interClusterDensity());
  }
 
  @Test
  public void testFuzzyKmeans() throws Exception {
    ClusteringTestUtils.writePointsToFile(sampleData, new Path(testdata, "file1"), fs, conf);
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        measure, numIterations, true);
    RepresentativePointsDriver.printRepresentativePoints(fuzzyKMeansOutput, numIterations);
    ClusterEvaluator evaluator = new ClusterEvaluator(conf, clustersIn);
    // now print out the Results
    System.out.println("Intra-cluster density = " + evaluator.intraClusterDensity());
    System.out.println("Inter-cluster density = " + evaluator.interClusterDensity());
  }
 
  @Test
  public void testMeanShift() throws Exception {
    ClusteringTestUtils.writePointsToFile(sampleData, new Path(testdata, "file1"), fs, conf);
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        numIterations, true);
    //printRepPoints(numIterations);
    ClusterEvaluator evaluator = new ClusterEvaluator(conf, clustersIn);
    // now print out the Results
    System.out.println("Intra-cluster density = " + evaluator.intraClusterDensity());
    System.out.println("Inter-cluster density = " + evaluator.interClusterDensity());
  }
 
  @Test
  public void testDirichlet() throws Exception {
    ClusteringTestUtils.writePointsToFile(sampleData, new Path(testdata, "file1"), fs, conf);
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        new EuclideanDistanceMeasure(), numIterations, true);
    //printRepPoints(numIterations);
    ClusterEvaluator evaluator = new ClusterEvaluator(conf, clustersIn);
    // now print out the Results
    System.out.println("Intra-cluster density = " + evaluator.intraClusterDensity());
    System.out.println("Inter-cluster density = " + evaluator.interClusterDensity());
  }
 
}
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    CanopyDriver.run(conf, testdata, output, measure, 3.1, 1.1, true, true);
    RepresentativePointsDriver.run(conf, clustersIn, new Path(output, "clusteredPoints"), output, measure, numIterations, true);
    printRepPoints(numIterations);
    ClusterEvaluator evaluatorSeq = new ClusterEvaluator(conf, clustersIn);
    // compare results
    assertEquals("InterCluster Density", evaluatorMR.interClusterDensity(), evaluatorSeq.interClusterDensity(), EPSILON);
    assertEquals("IntraCluster Density", evaluatorMR.intraClusterDensity(), evaluatorSeq.intraClusterDensity(), EPSILON);
  }

  @Test
  public void testCluster0() throws IOException {
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  public void testCluster0() throws IOException {
    ClusteringTestUtils.writePointsToFile(referenceData, new Path(testdata, "file1"), fs, conf);
    DistanceMeasure measure = new EuclideanDistanceMeasure();
    initData(1, 0.25, measure);
    ClusterEvaluator evaluator = new ClusterEvaluator(representativePoints, clusters, measure);
    assertEquals("inter cluster density", 0.33333333333333315, evaluator.interClusterDensity(), EPSILON);
    assertEquals("intra cluster density", 0.3656854249492381, evaluator.intraClusterDensity(), EPSILON);
  }

  @Test
  public void testCluster1() throws IOException {
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