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

Example 36 with Database

use of de.lmu.ifi.dbs.elki.database.Database 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 37 with Database

use of de.lmu.ifi.dbs.elki.database.Database 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 38 with Database

use of de.lmu.ifi.dbs.elki.database.Database 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 39 with Database

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

the class GriDBSCANTest method testGriDBSCANWide.

/**
 * Run DBSCAN with fixed parameters and compare the result to a golden
 * standard, with larger grid width (fewer cells, less redundancy).
 */
@Test
public void testGriDBSCANWide() {
    Database db = makeSimpleDatabase(UNITTEST + "3clusters-and-noise-2d.csv", 330);
    Clustering<Model> result = // 
    new ELKIBuilder<GriDBSCAN<DoubleVector>>(GriDBSCAN.class).with(DBSCAN.Parameterizer.EPSILON_ID, // 
    0.04).with(DBSCAN.Parameterizer.MINPTS_ID, // 
    20).with(GriDBSCAN.Parameterizer.GRID_ID, // 
    0.4).build().run(db);
    testFMeasure(db, result, 0.996413);
    testClusterSizes(result, new int[] { 29, 50, 101, 150 });
}

Example 40 with Database

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

the class GriDBSCANTest method testGriDBSCANResults.

/**
 * Run DBSCAN with fixed parameters and compare the result to a golden
 * standard.
 */
@Test
public void testGriDBSCANResults() {
    Database db = makeSimpleDatabase(UNITTEST + "3clusters-and-noise-2d.csv", 330);
    Clustering<Model> result = // 
    new ELKIBuilder<GriDBSCAN<DoubleVector>>(GriDBSCAN.class).with(DBSCAN.Parameterizer.EPSILON_ID, // 
    0.04).with(DBSCAN.Parameterizer.MINPTS_ID, // 
    20).with(GriDBSCAN.Parameterizer.GRID_ID, // 
    0.08).build().run(db);
    testFMeasure(db, result, 0.996413);
    testClusterSizes(result, new int[] { 29, 50, 101, 150 });
}