List of intraClusterDensity() Examples

Examples of intraClusterDensity()

org.apache.mahout.clustering.cdbw.CDbwEvaluator.intraClusterDensity()
The average density within clusters is defined as the percentage of representative points that reside in the neighborhood of the clusters' centers. The goal is the density within clusters to be significantly high. (eqn 5) @return a double
org.apache.mahout.clustering.evaluation.ClusterEvaluator.intraClusterDensity()
Computes the intra-cluster density as the average distance of the representative points from each other @return the intraClusterDensity of the representativePoints

Examples of org.apache.mahout.clustering.cdbw.CDbwEvaluator.intraClusterDensity()

        writer.append("\n");
        writer.append("Inter-Cluster Density: ").append(String.valueOf(ce.interClusterDensity())).append("\n");
        writer.append("Intra-Cluster Density: ").append(String.valueOf(ce.intraClusterDensity())).append("\n");
        CDbwEvaluator cdbw = new CDbwEvaluator(conf, seqFileDir);
        writer.append("CDbw Inter-Cluster Density: ").append(String.valueOf(cdbw.interClusterDensity())).append("\n");
        writer.append("CDbw Intra-Cluster Density: ").append(String.valueOf(cdbw.intraClusterDensity())).append("\n");
        writer.append("CDbw Separation: ").append(String.valueOf(cdbw.separation())).append("\n");
        writer.flush();
      }
      log.info("Wrote {} clusters", numWritten);
    } finally {

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Examples of org.apache.mahout.clustering.cdbw.CDbwEvaluator.intraClusterDensity()

        writer.append("\n");
        writer.append("Inter-Cluster Density: ").append(String.valueOf(ce.interClusterDensity())).append("\n");
        writer.append("Intra-Cluster Density: ").append(String.valueOf(ce.intraClusterDensity())).append("\n");
        CDbwEvaluator cdbw = new CDbwEvaluator(conf, seqFileDir);
        writer.append("CDbw Inter-Cluster Density: ").append(String.valueOf(cdbw.interClusterDensity())).append("\n");
        writer.append("CDbw Intra-Cluster Density: ").append(String.valueOf(cdbw.intraClusterDensity())).append("\n");
        writer.append("CDbw Separation: ").append(String.valueOf(cdbw.separation())).append("\n");
        writer.flush();
      }
      log.info("Wrote {} clusters", numWritten);
    } finally {

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

    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 {
    ClusteringTestUtils.writePointsToFile(referenceData, new Path(testdata, "file1"), fs, conf);

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

    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 {
    ClusteringTestUtils.writePointsToFile(referenceData, new Path(testdata, "file1"), fs, conf);

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

    ClusteringTestUtils.writePointsToFile(referenceData, new Path(testdata, "file1"), fs, conf);
    DistanceMeasure measure = new EuclideanDistanceMeasure();
    initData(1, 0.5, 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 testCluster2() throws IOException {
    ClusteringTestUtils.writePointsToFile(referenceData, new Path(testdata, "file1"), fs, conf);

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

    ClusteringTestUtils.writePointsToFile(referenceData, new Path(testdata, "file1"), fs, conf);
    DistanceMeasure measure = new EuclideanDistanceMeasure();
    initData(1, 0.75, 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 testEmptyCluster() throws IOException {
    ClusteringTestUtils.writePointsToFile(referenceData, new Path(testdata, "file1"), fs, conf);

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

    clusters.add(cluster);
    List<VectorWritable> points = new ArrayList<VectorWritable>();
    representativePoints.put(cluster.getId(), points);
    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 testSingleValueCluster() throws IOException {
    ClusteringTestUtils.writePointsToFile(referenceData, new Path(testdata, "file1"), fs, conf);

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

    List<VectorWritable> points = new ArrayList<VectorWritable>();
    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", 0.33333333333333315, 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 clusters should be ignored like empty clusters above

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

    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", 0.33333333333333315, evaluator.interClusterDensity(), EPSILON);
    assertEquals("intra cluster density", 0.3656854249492381, evaluator.intraClusterDensity(), EPSILON);
  }


  @Test
  public void testCanopy() throws Exception {
    ClusteringTestUtils.writePointsToFile(sampleData, new Path(testdata, "file1"), fs, conf);

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

    int numIterations = 10;
    Path clustersIn = new Path(output, "clusters-0");
    RepresentativePointsDriver.run(conf, clustersIn, new Path(output, "clusteredPoints"), output, measure, numIterations, true);
    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());


    printRepPoints(numIterations);
  }

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