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 testDiSHSubspaceOverlapping() {
    Database db = makeSimpleDatabase(UNITTEST + "subspace-overlapping-4-5d.ascii", 1100);

    // Setup algorithm
    ListParameterization params = new ListParameterization();
    params.addParameter(DiSH.EPSILON_ID, 0.1);
    params.addParameter(DiSH.MU_ID, 30);
    DiSH<DoubleVector> dish = ClassGenericsUtil.parameterizeOrAbort(DiSH.class, params);
    testParameterizationOk(params);

    // run DiSH on database
    Clustering<SubspaceModel<DoubleVector>> result = dish.run(db);
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   */
  @Test
  public void testCLIQUEResults() {
    Database db = makeSimpleDatabase(UNITTEST + "subspace-simple.csv", 600);

    ListParameterization params = new ListParameterization();
    params.addParameter(CLIQUE.TAU_ID, "0.1");
    params.addParameter(CLIQUE.XSI_ID, 20);

    // setup algorithm
    CLIQUE<DoubleVector> clique = ClassGenericsUtil.parameterizeOrAbort(CLIQUE.class, params);
    testParameterizationOk(params);

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  @Test
  public void testFeatureBaggingSum() {
    Database db = makeSimpleDatabase(UNITTEST + "outlier-axis-subspaces-6d.ascii", 1345);

    // Parameterization
    ListParameterization params = new ListParameterization();
    params.addParameter(LOF.K_ID, 10);
    params.addParameter(FeatureBagging.Parameterizer.NUM_ID, 10);
    params.addParameter(FeatureBagging.Parameterizer.SEED_ID, 1);

    // setup Algorithm
    FeatureBagging fb = ClassGenericsUtil.parameterizeOrAbort(FeatureBagging.class, params);
    testParameterizationOk(params);
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  @Test
  public void testCLIQUESubspaceOverlapping() {
    Database db = makeSimpleDatabase(UNITTEST + "subspace-overlapping-3-4d.ascii", 850);

    // Setup algorithm
    ListParameterization params = new ListParameterization();
    params.addParameter(CLIQUE.TAU_ID, 0.2);
    params.addParameter(CLIQUE.XSI_ID, 6);
    CLIQUE<DoubleVector> clique = ClassGenericsUtil.parameterizeOrAbort(CLIQUE.class, params);
    testParameterizationOk(params);

    // run CLIQUE on database
    Clustering<SubspaceModel<DoubleVector>> result = clique.run(db);
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  @Test
  public void testFeatureBaggingBreadth() {
    Database db = makeSimpleDatabase(UNITTEST + "outlier-axis-subspaces-6d.ascii", 1345);

    // Parameterization
    ListParameterization params = new ListParameterization();
    params.addParameter(LOF.K_ID, 10);
    params.addParameter(FeatureBagging.Parameterizer.NUM_ID, 10);
    params.addParameter(FeatureBagging.Parameterizer.SEED_ID, 5);
    params.addFlag(FeatureBagging.Parameterizer.BREADTH_ID);

    // setup Algorithm
    FeatureBagging fb = ClassGenericsUtil.parameterizeOrAbort(FeatureBagging.class, params);
    testParameterizationOk(params);
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  @Test
  public void testDBSCANResults() {
    Database db = makeSimpleDatabase(UNITTEST + "3clusters-and-noise-2d.csv", 330);

    // setup algorithm
    ListParameterization params = new ListParameterization();
    params.addParameter(DBSCAN.EPSILON_ID, 0.04);
    params.addParameter(DBSCAN.MINPTS_ID, 20);
    DBSCAN<DoubleVector, DoubleDistance> dbscan = ClassGenericsUtil.parameterizeOrAbort(DBSCAN.class, params);
    testParameterizationOk(params);

    // run DBSCAN on database
    Clustering<Model> result = dbscan.run(db);
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  @Test
  public void testDBSCANOnSingleLinkDataset() {
    Database db = makeSimpleDatabase(UNITTEST + "single-link-effect.ascii", 638);

    // Setup algorithm
    ListParameterization params = new ListParameterization();
    params.addParameter(DBSCAN.EPSILON_ID, 11.5);
    params.addParameter(DBSCAN.MINPTS_ID, 120);
    DBSCAN<DoubleVector, DoubleDistance> dbscan = ClassGenericsUtil.parameterizeOrAbort(DBSCAN.class, params);
    testParameterizationOk(params);

    // run DBSCAN on database
    Clustering<Model> result = dbscan.run(db);
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   */
  @Test
  public void testSUBCLUResults() {
    Database db = makeSimpleDatabase(UNITTEST + "subspace-simple.csv", 600);

    ListParameterization params = new ListParameterization();
    params.addParameter(SUBCLU.EPSILON_ID, 0.001);
    params.addParameter(SUBCLU.MINPTS_ID, 100);

    // setup algorithm
    SUBCLU<DoubleVector> subclu = ClassGenericsUtil.parameterizeOrAbort(SUBCLU.class, params);
    testParameterizationOk(params);

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  @Test
  public void testSUBCLUSubspaceOverlapping() {
    Database db = makeSimpleDatabase(UNITTEST + "subspace-overlapping-3-4d.ascii", 850);

    // Setup algorithm
    ListParameterization params = new ListParameterization();
    params.addParameter(SUBCLU.EPSILON_ID, 0.04);
    params.addParameter(SUBCLU.MINPTS_ID, 70);
    SUBCLU<DoubleVector> subclu = ClassGenericsUtil.parameterizeOrAbort(SUBCLU.class, params);
    testParameterizationOk(params);

    // run SUBCLU on database
    Clustering<SubspaceModel<DoubleVector>> result = subclu.run(db);
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  @Test
  public void testSNNClusteringResults() {
    Database db = makeSimpleDatabase(UNITTEST + "different-densities-2d.ascii", 1200);

    // Setup algorithm
    ListParameterization params = new ListParameterization();
    params.addParameter(SNNClustering.EPSILON_ID, 77);
    params.addParameter(SNNClustering.MINPTS_ID, 28);
    params.addParameter(SharedNearestNeighborPreprocessor.Factory.NUMBER_OF_NEIGHBORS_ID, 100);
    SNNClustering<DoubleVector> snn = ClassGenericsUtil.parameterizeOrAbort(SNNClustering.class, params);
    testParameterizationOk(params);

    // run SNN on database
    Clustering<Model> result = snn.run(db);
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Related Classes of de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ListParameterization

  • de.lmu.ifi.dbs.elki.algorithm.AbstractSimpleAlgorithmTest
  • de.lmu.ifi.dbs.elki.algorithm.clustering.AbstractProjectedDBSCAN$Parameterizer
  • de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.CASH
  • de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.COPAC
  • de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.COPAC$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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