Examples of ClusterEvaluator

org.apache.mahout.clustering.evaluation.ClusterEvaluator

Examples of org.apache.mahout.clustering.evaluation.ClusterEvaluator

    Configuration conf = new Configuration();
    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-10");
    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);
  }

View Full Code Here

Examples of org.apache.mahout.clustering.evaluation.ClusterEvaluator

                                   new Path(output, "clusteredPoints"),
                                   output,
                                   new EuclideanDistanceMeasure(),
                                   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);
  }

View Full Code Here

Examples of org.apache.mahout.clustering.evaluation.ClusterEvaluator

                "--distanceMeasure", measure.getClass().getName(),
                "--maxIter", String.valueOf(numIters)//
        });
        conf.set(RepresentativePointsDriver.DISTANCE_MEASURE_KEY, measure.getClass().getName());
        conf.set(RepresentativePointsDriver.STATE_IN_KEY, "tmp/representative/representativePoints-" + numIters);
        ClusterEvaluator ce = new ClusterEvaluator(conf, seqFileDir);
        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();

View Full Code Here

Examples of org.apache.mahout.clustering.evaluation.ClusterEvaluator

    int numIterations = 2;
    Path clustersIn = new Path(output, "clusters-0-final");
    RepresentativePointsDriver.run(conf, clustersIn, new Path(output,
        "clusteredPoints"), output, measure, numIterations, false);
    printRepPoints(numIterations);
    ClusterEvaluator evaluatorMR = new ClusterEvaluator(conf, clustersIn);
    // now run again using sequential reference point calculation
    HadoopUtil.delete(conf, output);
    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);
  }

View Full Code Here

Examples of org.apache.mahout.clustering.evaluation.ClusterEvaluator

  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);
  }

View Full Code Here

Examples of org.apache.mahout.clustering.evaluation.ClusterEvaluator

  public void testCluster1() throws IOException {
    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);
  }

View Full Code Here

Examples of org.apache.mahout.clustering.evaluation.ClusterEvaluator

  public void testCluster2() throws IOException {
    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);
  }

View Full Code Here

Examples of org.apache.mahout.clustering.evaluation.ClusterEvaluator

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

View Full Code Here

Examples of org.apache.mahout.clustering.evaluation.ClusterEvaluator

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

View Full Code Here

Examples of org.apache.mahout.clustering.evaluation.ClusterEvaluator

    List<VectorWritable> points = Lists.newArrayList();
    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", 0.33333333333333315,
        evaluator.interClusterDensity(), EPSILON);
    assertEquals("intra cluster density", 0.3656854249492381,
        evaluator.intraClusterDensity(), EPSILON);
  }

View Full Code Here

0 1 2 3 4 5

TOP

All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.