Examples with DoubleVector de.lmu.ifi.dbs.elki.data.DoubleVector used on opensource projects

Example 1 with DoubleVector

use of de.lmu.ifi.dbs.elki.data.DoubleVector 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 DoubleVector

use of de.lmu.ifi.dbs.elki.data.DoubleVector 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 DoubleVector

use of de.lmu.ifi.dbs.elki.data.DoubleVector 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 DoubleVector

use of de.lmu.ifi.dbs.elki.data.DoubleVector in project elki by elki-project.

the class CLARANSTest method testCLARANSNoise.

@Test
public void testCLARANSNoise() {
    Database db = makeSimpleDatabase(UNITTEST + "3clusters-and-noise-2d.csv", 330);
    Clustering<MedoidModel> result = // 
    new ELKIBuilder<CLARANS<DoubleVector>>(CLARANS.class).with(KMeans.K_ID, // 
    3).with(CLARANS.Parameterizer.RANDOM_ID, // 
    0).with(CLARANS.Parameterizer.NEIGHBORS_ID, // 
    .1).with(CLARANS.Parameterizer.RESTARTS_ID, // 
    5).build().run(db);
    testFMeasure(db, result, 0.913858);
    testClusterSizes(result, new int[] { 57, 115, 158 });
}

Example 5 with DoubleVector

use of de.lmu.ifi.dbs.elki.data.DoubleVector in project elki by elki-project.

the class CLARATest method testCLARA.

/**
 * Run CLARA with fixed parameters and compare the result to a golden
 * standard.
 */
@Test
public void testCLARA() {
    Database db = makeSimpleDatabase(UNITTEST + "different-densities-2d-no-noise.ascii", 1000);
    Clustering<MedoidModel> result = // 
    new ELKIBuilder<CLARA<DoubleVector>>(CLARA.class).with(KMeans.K_ID, // 
    5).with(CLARA.Parameterizer.RANDOM_ID, // 
    1).with(CLARA.Parameterizer.NUMSAMPLES_ID, // 
    2).with(CLARA.Parameterizer.SAMPLESIZE_ID, // 
    50).build().run(db);
    testFMeasure(db, result, 0.998005);
    testClusterSizes(result, new int[] { 199, 200, 200, 200, 201 });
}