Examples with Database de.lmu.ifi.dbs.elki.database.Database used on opensource projects

Example 6 with Database

use of de.lmu.ifi.dbs.elki.database.Database 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 7 with Database

use of de.lmu.ifi.dbs.elki.database.Database 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 8 with Database

use of de.lmu.ifi.dbs.elki.database.Database 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 9 with Database

use of de.lmu.ifi.dbs.elki.database.Database in project elki by elki-project.

the class AGNESTest method testSingleLink.

// TODO: add more data sets.
/**
 * Run agglomerative hierarchical clustering with fixed parameters and compare
 * the result to a golden standard.
 */
@Test
public void testSingleLink() {
    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, // 
    SingleLinkage.class).build().run(db);
    testFMeasure(db, clustering, 0.6829722);
    testClusterSizes(clustering, new int[] { 9, 200, 429 });
}

Example 10 with Database

use of de.lmu.ifi.dbs.elki.database.Database in project elki by elki-project.

the class AGNESTest method testCompleteLink.

/**
 * Run agglomerative hierarchical clustering with fixed parameters and compare
 * the result to a golden standard.
 */
@Test
public void testCompleteLink() {
    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, // 
    CompleteLinkage.class).build().run(db);
    testFMeasure(db, clustering, 0.938167802);
    testClusterSizes(clustering, new int[] { 200, 217, 221 });
}