Package org.apache.mahout.clustering.kernel

Examples of org.apache.mahout.clustering.kernel.IKernelProfile

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    double t1 = Double.parseDouble(getOption(DefaultOptionCreator.T1_OPTION));
    double t2 = Double.parseDouble(getOption(DefaultOptionCreator.T2_OPTION));
    double convergenceDelta = Double.parseDouble(getOption(DefaultOptionCreator.CONVERGENCE_DELTA_OPTION));
    int maxIterations = Integer.parseInt(getOption(DefaultOptionCreator.MAX_ITERATIONS_OPTION));
    DistanceMeasure measure = ClassUtils.instantiateAs(measureClass, DistanceMeasure.class);
    IKernelProfile kernelProfile = ClassUtils.instantiateAs(kernelProfileClass, IKernelProfile.class);
    run(getConf(), input, output, measure, kernelProfile, t1, t2, convergenceDelta, maxIterations);
    return 0;
  }
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        .parseInt(getOption(DefaultOptionCreator.MAX_ITERATIONS_OPTION));
    boolean inputIsCanopies = hasOption(INPUT_IS_CANOPIES_OPTION);
    boolean runSequential = getOption(DefaultOptionCreator.METHOD_OPTION)
        .equalsIgnoreCase(DefaultOptionCreator.SEQUENTIAL_METHOD);
    DistanceMeasure measure = ClassUtils.instantiateAs(measureClass, DistanceMeasure.class);
    IKernelProfile kernelProfile = ClassUtils.instantiateAs(kernelProfileClass, IKernelProfile.class);
    run(getConf(), input, output, measure, kernelProfile, t1, t2,
        convergenceDelta, maxIterations, inputIsCanopies, runClustering,
        runSequential);

    return 0;
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  public static void main(String[] args) throws Exception {
    t1 = 1.5;
    t2 = 0.5;
    DistanceMeasure measure = new EuclideanDistanceMeasure();
    IKernelProfile kernelProfile = new TriangularKernelProfile();
    significance = 0.02;
   
    Path samples = new Path("samples");
    Path output = new Path("output");
    Configuration conf = new Configuration();
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  @Test
  public void testMeanShift() throws Exception {
    ClusteringTestUtils.writePointsToFile(sampleData, getTestTempFilePath("testdata/file1"), fs, conf);
    DistanceMeasure measure = new EuclideanDistanceMeasure();
    IKernelProfile kernelProfile = new TriangularKernelProfile();
    MeanShiftCanopyDriver.run(conf, testdata, output, measure, kernelProfile, 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);
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  }
 
  @Test
  public void testMeanShift() throws Exception {
    DistanceMeasure measure = new CosineDistanceMeasure();
    IKernelProfile kernelProfile = new TriangularKernelProfile();
    Path output = getTestTempDirPath("output");
    Configuration conf = new Configuration();
    MeanShiftCanopyDriver.run(conf, getTestTempDirPath("testdata"), output,
        measure, kernelProfile, 0.5, 0.01, 0.05, 10, false, true, true);
    // run ClusterDumper
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  @Test
  public void testMeanShift() throws Exception {
    ClusteringTestUtils.writePointsToFile(sampleData, new Path(testdata, "file1"), fs, conf);
    DistanceMeasure measure = new EuclideanDistanceMeasure();
    IKernelProfile kernelProfile = new TriangularKernelProfile();
    Configuration conf = new Configuration();
    MeanShiftCanopyDriver.run(conf, testdata, output, measure, kernelProfile, 2.1, 1.0, 0.001, 10, false, true, true);
    int numIterations = 10;
    Path clustersIn = new Path(output, "clusters-8-final");
    RepresentativePointsDriver.run(conf, clustersIn, new Path(output, "clusteredPoints"), output, measure,
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Related Classes of org.apache.mahout.clustering.kernel.IKernelProfile

  • org.apache.mahout.clustering.cdbw.TestCDbwEvaluator
  • org.apache.mahout.clustering.display.DisplayMeanShift
  • org.apache.mahout.clustering.meanshift.MeanShiftCanopyDriver
  • org.apache.mahout.clustering.syntheticcontrol.meanshift.Job
  • org.apache.mahout.clustering.TestClusterDumper
  • org.apache.mahout.clustering.TestClusterEvaluator
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