Examples with ELKIBuilder de.lmu.ifi.dbs.elki.utilities.ELKIBuilder used on opensource projects

Example 1 with ELKIBuilder

use of de.lmu.ifi.dbs.elki.utilities.ELKIBuilder in project elki by elki-project.

the class EMTest method testEMMLEMultivariate.

@Test
public void testEMMLEMultivariate() {
    Database db = makeSimpleDatabase(UNITTEST + "hierarchical-2d.ascii", 710);
    Clustering<?> result = // 
    new ELKIBuilder<EM<DoubleVector, ?>>(EM.class).with(KMeans.SEED_ID, // 
    0).with(EM.Parameterizer.K_ID, // 
    6).build().run(db);
    testFMeasure(db, result, 0.967410486);
    testClusterSizes(result, new int[] { 3, 5, 91, 98, 200, 313 });
}

Example 2 with ELKIBuilder

use of de.lmu.ifi.dbs.elki.utilities.ELKIBuilder in project elki by elki-project.

the class EMTest method testEMMAPDiagonal.

@Test
public void testEMMAPDiagonal() {
    Database db = makeSimpleDatabase(UNITTEST + "hierarchical-2d.ascii", 710);
    Clustering<?> result = // 
    new ELKIBuilder<EM<DoubleVector, ?>>(EM.class).with(KMeans.SEED_ID, // 
    3).with(EM.Parameterizer.K_ID, // 
    5).with(EM.Parameterizer.INIT_ID, // 
    DiagonalGaussianModelFactory.class).with(EM.Parameterizer.PRIOR_ID, // 
    10).build().run(db);
    testFMeasure(db, result, 0.949566);
    testClusterSizes(result, new int[] { 6, 97, 98, 202, 307 });
}

Example 3 with ELKIBuilder

use of de.lmu.ifi.dbs.elki.utilities.ELKIBuilder in project elki by elki-project.

the class LSDBCTest method testLSDBCResults.

@Test
public void testLSDBCResults() {
    Database db = makeSimpleDatabase(UNITTEST + "3clusters-and-noise-2d.csv", 330);
    Clustering<Model> result = // 
    new ELKIBuilder<LSDBC<DoubleVector>>(LSDBC.class).with(LSDBC.Parameterizer.ALPHA_ID, // 
    0.4).with(LSDBC.Parameterizer.K_ID, // 
    20).build().run(db);
    testFMeasure(db, result, 0.44848979);
    testClusterSizes(result, new int[] { 38, 38, 41, 54, 159 });
}

Example 4 with ELKIBuilder

use of de.lmu.ifi.dbs.elki.utilities.ELKIBuilder in project elki by elki-project.

the class AGNESTest method testBetaVariance.

/**
 * Run agglomerative hierarchical clustering with fixed parameters and compare
 * the result to a golden standard.
 */
@Test
public void testBetaVariance() {
    Database db = makeSimpleDatabase(UNITTEST + "single-link-effect.ascii", 638);
    Clustering<?> clustering = // 
    new ELKIBuilder<>(CutDendrogramByNumberOfClusters.class).with(CutDendrogramByNumberOfClusters.Parameterizer.MINCLUSTERS_ID, // 
    3).with(AbstractAlgorithm.ALGORITHM_ID, // 
    AGNES.class).with(AGNES.Parameterizer.LINKAGE_ID, // 
    FlexibleBetaLinkage.class).with(FlexibleBetaLinkage.Parameterizer.BETA_ID, // 
    -.33).build().run(db);
    testFMeasure(db, clustering, 0.9277466);
    testClusterSizes(clustering, new int[] { 196, 200, 242 });
}

Example 5 with ELKIBuilder

use of de.lmu.ifi.dbs.elki.utilities.ELKIBuilder in project elki by elki-project.

the class MiniMaxAnderbergTest method testMiniMax.

// TODO: add more data sets.
/**
 * Run agglomerative hierarchical clustering with fixed parameters and compare
 * the result to a golden standard.
 */
@Test
public void testMiniMax() {
    Database db = makeSimpleDatabase(UNITTEST + "single-link-effect.ascii", 638);
    Clustering<?> clustering = // 
    new ELKIBuilder<>(CutDendrogramByNumberOfClusters.class).with(CutDendrogramByNumberOfClusters.Parameterizer.MINCLUSTERS_ID, // 
    3).with(AbstractAlgorithm.ALGORITHM_ID, // 
    MiniMaxAnderberg.class).build().run(db);
    testFMeasure(db, clustering, 0.938662648);
    testClusterSizes(clustering, new int[] { 200, 211, 227 });
}