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

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

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  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
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    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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  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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  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
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    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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  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);
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    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
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    // 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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   */
  @Test
  public void testCASHResults() {
    ListParameterization inp = new ListParameterization();
    // CASH input
    inp.addParameter(FileBasedDatabaseConnection.PARSER_ID, ParameterizationFunctionLabelParser.class);
    // Input
    Database db = makeSimpleDatabase(UNITTEST + "hierarchical-3d2d1d.csv", 600, inp, null);

    // CASH parameters
    ListParameterization params = new ListParameterization();
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