Package de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization

Examples of de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ListParameterization

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  @Test
  public void testDBOutlierDetection() {
    Database db = makeSimpleDatabase(UNITTEST + "outlier-fire.ascii", 1025);

    // Parameterization
    ListParameterization params = new ListParameterization();
    params.addParameter(DBOutlierDetection.D_ID, 0.175);
    params.addParameter(DBOutlierDetection.P_ID, 0.98);

    // setup Algorithm
    DBOutlierDetection<DoubleVector, DoubleDistance> dbOutlierDetection = ClassGenericsUtil.parameterizeOrAbort(DBOutlierDetection.class, params);
    testParameterizationOk(params);
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  @Test
  public void testKNNWeightOutlier() {
    Database db = makeSimpleDatabase(UNITTEST + "outlier-3d-3clusters.ascii", 960);

    // Parameterization
    ListParameterization params = new ListParameterization();
    params.addParameter(KNNWeightOutlier.K_ID, 5);

    // setup Algorithm
    KNNWeightOutlier<DoubleVector, DoubleDistance> knnWeightOutlier = ClassGenericsUtil.parameterizeOrAbort(KNNWeightOutlier.class, params);
    testParameterizationOk(params);
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  /**
   * Returns the database.
   */
  private static UpdatableDatabase getDatabase() {
    ListParameterization params = new ListParameterization();
    params.addParameter(FileBasedDatabaseConnection.INPUT_ID, dataset);

    UpdatableDatabase db = ClassGenericsUtil.parameterizeOrAbort(HashmapDatabase.class, params);
    params.failOnErrors();
    if(params.hasUnusedParameters()) {
      fail("Unused parameters: " + params.getRemainingParameters());
    }

    // get database
    db.initialize();
    return db;
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  @Test
  public void testLOF() {
    Database db = makeSimpleDatabase(UNITTEST + "outlier-axis-subspaces-6d.ascii", 1345);

    // Parameterization
    ListParameterization params = new ListParameterization();
    params.addParameter(LOF.K_ID, 10);

    // setup Algorithm
    LOF<DoubleVector, DoubleDistance> lof = ClassGenericsUtil.parameterizeOrAbort(LOF.class, params);
    testParameterizationOk(params);
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  @Test
  public void testLOCI() {
    Database db = makeSimpleDatabase(UNITTEST + "3clusters-and-noise-2d.csv", 330);

    // Parameterization
    ListParameterization params = new ListParameterization();
    params.addParameter(LOCI.RMAX_ID, 0.5);

    // setup Algorithm
    LOCI<DoubleVector, DoubleDistance> loci = ClassGenericsUtil.parameterizeOrAbort(LOCI.class, params);
    testParameterizationOk(params);
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  @Test
  public void testDBOutlierScore() {
    Database db = makeSimpleDatabase(UNITTEST + "outlier-fire.ascii", 1025);

    // Parameterization
    ListParameterization params = new ListParameterization();
    params.addParameter(DBOutlierScore.D_ID, 0.175);

    // setup Algorithm
    DBOutlierScore<DoubleVector, DoubleDistance> dbOutlierScore = ClassGenericsUtil.parameterizeOrAbort(DBOutlierScore.class, params);
    testParameterizationOk(params);
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  @Test
  public void testKNNOutlier() {
    Database db = makeSimpleDatabase(UNITTEST + "outlier-3d-3clusters.ascii", 960);

    // Parameterization
    ListParameterization params = new ListParameterization();
    params.addParameter(KNNOutlier.K_ID, 2);

    // setup Algorithm
    KNNOutlier<DoubleVector, DoubleDistance> knnOutlier = ClassGenericsUtil.parameterizeOrAbort(KNNOutlier.class, params);
    testParameterizationOk(params);
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  @Test
  public void testSOD() {
    Database db = makeSimpleDatabase(UNITTEST + "outlier-axis-subspaces-6d.ascii", 1345);

    // Parameterization
    ListParameterization params = new ListParameterization();
    params.addParameter(SOD.KNN_ID, 25);
    params.addParameter(SharedNearestNeighborPreprocessor.Factory.NUMBER_OF_NEIGHBORS_ID, 19);

    // setup Algorithm
    SOD<DoubleVector> sod = ClassGenericsUtil.parameterizeOrAbort(SOD.class, params);
    testParameterizationOk(params);
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  @Test
  public void testINFLO() {
    Database db = makeSimpleDatabase(UNITTEST + "outlier-3d-3clusters.ascii", 960);

    // Parameterization
    ListParameterization params = new ListParameterization();
    params.addParameter(INFLO.K_ID, 29);

    // setup Algorithm
    INFLO<DoubleVector, DoubleDistance> inflo = ClassGenericsUtil.parameterizeOrAbort(INFLO.class, params);
    testParameterizationOk(params);
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  @Test
  public void testAggarwalYuNaive() {
    Database db = makeSimpleDatabase(UNITTEST + "outlier-3d-3clusters.ascii", 960);

    // Parameterization
    ListParameterization params = new ListParameterization();
    params.addParameter(AggarwalYuNaive.K_ID, 2);
    params.addParameter(AggarwalYuNaive.PHI_ID, 8);

    // setup Algorithm
    AggarwalYuNaive<DoubleVector> aggarwalYuNaive = ClassGenericsUtil.parameterizeOrAbort(AggarwalYuNaive.class, params);
    testParameterizationOk(params);
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Related Classes of de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ListParameterization

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  • de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.COPAC
  • de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.COPAC$Parameterizer
  • de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.ERiC
  • de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.HiCO$Parameterizer
  • de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.TestCASHResults
  • de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.TestCOPACResults
  • de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.TestERiCResults
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