Examples of DistanceMeasure

com.aamend.hadoop.clustering.distance.DistanceMeasure
Author: antoine.amend@gmail.com Date: 21/03/14
org.apache.commons.math3.ml.distance.DistanceMeasure
Interface for distance measures of n-dimensional vectors. @since 3.2
org.apache.mahout.common.distance.DistanceMeasure
This interface is used for objects which can determine a distance metric between two points
org.apache.mahout.utils.DistanceMeasure
This interface is used for objects which can determine a distance metric between two points

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

  }


  @Test
  public void testCDbw2() throws IOException {
    ClusteringTestUtils.writePointsToFile(referenceData, getTestTempFilePath("testdata/file1"), fs, conf);
    DistanceMeasure measure = new EuclideanDistanceMeasure();
    initData(1, 0.75, measure);
    CDbwEvaluator evaluator = new CDbwEvaluator(representativePoints, clusters, measure);
    assertEquals("inter cluster density", 0.682842712474619, evaluator.interClusterDensity(), EPSILON);
    assertEquals("separation", 4.0576740025245694, evaluator.separation(), EPSILON);
    assertEquals("intra cluster density", 0.26666666666666666, evaluator.intraClusterDensity(), EPSILON);

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

  }


  @Test
  public void testEmptyCluster() throws IOException {
    ClusteringTestUtils.writePointsToFile(referenceData, getTestTempFilePath("testdata/file1"), fs, conf);
    DistanceMeasure measure = new EuclideanDistanceMeasure();
    initData(1, 0.25, measure);
    Canopy cluster = new Canopy(new DenseVector(new double[] { 10, 10 }), 19, measure);
    clusters.add(cluster);
    List<VectorWritable> points = new ArrayList<VectorWritable>();
    representativePoints.put(cluster.getId(), points);

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

  }


  @Test
  public void testSingleValueCluster() throws IOException {
    ClusteringTestUtils.writePointsToFile(referenceData, getTestTempFilePath("testdata/file1"), fs, conf);
    DistanceMeasure measure = new EuclideanDistanceMeasure();
    initData(1, 0.25, measure);
    Canopy cluster = new Canopy(new DenseVector(new double[] { 0, 0 }), 19, measure);
    clusters.add(cluster);
    List<VectorWritable> points = new ArrayList<VectorWritable>();
    points.add(new VectorWritable(cluster.getCenter().plus(new DenseVector(new double[] { 1, 1 }))));

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

   * @throws IOException 
   */
  @Test
  public void testAllSameValueCluster() throws IOException {
    ClusteringTestUtils.writePointsToFile(referenceData, getTestTempFilePath("testdata/file1"), fs, conf);
    DistanceMeasure measure = new EuclideanDistanceMeasure();
    initData(1, 0.25, measure);
    Canopy cluster = new Canopy(new DenseVector(new double[] { 0, 0 }), 19, measure);
    clusters.add(cluster);
    List<VectorWritable> points = new ArrayList<VectorWritable>();
    points.add(new VectorWritable(cluster.getCenter()));

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

   * @throws IOException 
   */
  @Test
  public void testAlmostSameValueCluster() throws IOException {
    ClusteringTestUtils.writePointsToFile(referenceData, getTestTempFilePath("testdata/file1"), fs, conf);
    DistanceMeasure measure = new EuclideanDistanceMeasure();
    initData(1, 0.25, measure);
    Canopy cluster = new Canopy(new DenseVector(new double[] { 0, 0 }), 19, measure);
    clusters.add(cluster);
    List<VectorWritable> points = new ArrayList<VectorWritable>();
    Vector delta = new DenseVector(new double[] { 0, Double.MIN_NORMAL });

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

  }


  @Test
  public void testCanopy() throws Exception {
    ClusteringTestUtils.writePointsToFile(sampleData, getTestTempFilePath("testdata/file1"), fs, conf);
    DistanceMeasure measure = new EuclideanDistanceMeasure();
    CanopyDriver.run(new Configuration(), testdata, output, measure, 3.1, 2.1, true, true);
    int numIterations = 10;
    Path clustersIn = new Path(output, "clusters-0");
    RepresentativePointsDriver.run(conf, clustersIn, new Path(output, "clusteredPoints"), output, measure, numIterations, true);
    CDbwEvaluator evaluator = new CDbwEvaluator(conf, clustersIn);

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

  }


  @Test
  public void testKmeans() throws Exception {
    ClusteringTestUtils.writePointsToFile(sampleData, getTestTempFilePath("testdata/file1"), fs, conf);
    DistanceMeasure measure = new EuclideanDistanceMeasure();
    // now run the Canopy job to prime kMeans canopies
    CanopyDriver.run(new Configuration(), testdata, output, measure, 3.1, 2.1, false, true);
    // now run the KMeans job
    KMeansDriver.run(testdata, new Path(output, "clusters-0"), output, measure, 0.001, 10, true, true);
    int numIterations = 10;

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

  }


  @Test
  public void testFuzzyKmeans() throws Exception {
    ClusteringTestUtils.writePointsToFile(sampleData, getTestTempFilePath("testdata/file1"), fs, conf);
    DistanceMeasure measure = new EuclideanDistanceMeasure();
    // now run the Canopy job to prime kMeans canopies
    CanopyDriver.run(new Configuration(), testdata, output, measure, 3.1, 2.1, false, true);
    // now run the KMeans job
    FuzzyKMeansDriver.run(testdata, new Path(output, "clusters-0"), output, measure, 0.001, 10, 2, true, true, 0, true);
    int numIterations = 10;

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

  }


  @Test
  public void testMeanShift() throws Exception {
    ClusteringTestUtils.writePointsToFile(sampleData, getTestTempFilePath("testdata/file1"), fs, conf);
    DistanceMeasure measure = new EuclideanDistanceMeasure();
    new MeanShiftCanopyDriver().run(conf, testdata, output, measure, 2.1, 1.0, 0.001, 10, false, true, true);
    int numIterations = 10;
    Path clustersIn = new Path(output, "clusters-2");
    RepresentativePointsDriver.run(conf, clustersIn, new Path(output, "clusteredPoints"), output, measure, numIterations, true);
    CDbwEvaluator evaluator = new CDbwEvaluator(conf, clustersIn);

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

      }


      // 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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