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

Example 16 with ELKIBuilder

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

the class KMeansHybridLloydMacQueenTest method testKMeansHybridLloydMacQueen.

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

Example 17 with ELKIBuilder

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

the class KMeansMacQueenTest method testKMeansMacQueen.

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

Example 18 with ELKIBuilder

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

the class KMeansSortTest method testKMeansSort.

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

Example 19 with ELKIBuilder

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

the class FourCTest method testFourCResults.

/**
 * Run 4C with fixed parameters and compare the result to a golden standard.
 */
@Test
public void testFourCResults() {
    Database db = makeSimpleDatabase(UNITTEST + "hierarchical-3d2d1d.csv", 600);
    Clustering<Model> result = // 
    new ELKIBuilder<FourC<DoubleVector>>(FourC.class).with(DBSCAN.Parameterizer.EPSILON_ID, // 
    0.30).with(DBSCAN.Parameterizer.MINPTS_ID, // 
    50).with(LimitEigenPairFilter.Parameterizer.EIGENPAIR_FILTER_DELTA, // 
    0.5).with(FourC.Settings.Parameterizer.LAMBDA_ID, // 
    1).build().run(db);
    testFMeasure(db, result, 0.7052);
    testClusterSizes(result, new int[] { 218, 382 });
}

Example 20 with ELKIBuilder

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

the class GeneralizedDBSCANTest method testDBSCANOnSingleLinkDataset.

/**
 * Run Generalized DBSCAN with fixed parameters and compare the result to a
 * golden standard.
 */
@Test
public void testDBSCANOnSingleLinkDataset() {
    Database db = makeSimpleDatabase(UNITTEST + "single-link-effect.ascii", 638);
    Clustering<Model> result = // 
    new ELKIBuilder<>(GeneralizedDBSCAN.class).with(DBSCAN.Parameterizer.EPSILON_ID, // 
    11.5).with(DBSCAN.Parameterizer.MINPTS_ID, // 
    120).build().run(db);
    testFMeasure(db, result, 0.954382);
    testClusterSizes(result, new int[] { 11, 200, 203, 224 });
}