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.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);
  }
  
  /**
   * adding an empty cluster should modify the inter cluster density but not change the intra-cluster density as that
   * cluster would have NaN as its intra-cluster density and NaN values are ignored by the evaluator

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

    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
   * that cluster would have NaN as its intra-cluster density and NaN values are ignored by the evaluator

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

    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
   * clusters are included in the inter-cluster density but their NaN intra-density values are ignored by the evaluator.

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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", 0.3656854249492381, 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()

    RepresentativePointsDriver.run(conf, clustersIn, new Path(output, "clusteredPoints"), output, measure,
        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 {

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

    RepresentativePointsDriver.run(conf, clustersIn, new Path(kmeansOutput, "clusteredPoints"), kmeansOutput, measure,
        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 {

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

    RepresentativePointsDriver.run(conf, clustersIn, new Path(fuzzyKMeansOutput, "clusteredPoints"), fuzzyKMeansOutput,
        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 {

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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 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 {

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

    RepresentativePointsDriver.run(conf, clustersIn, new Path(output, "clusteredPoints"), output,
        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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