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

Example 6 with DoubleVector

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

the class KMeansBisectingTest method testKMeansBisectingFMeasure.

/**
 * Run KMeansBisecting with fixed parameters (k = 2) and compare f-measure to
 * golden standard.
 */
@Test
public void testKMeansBisectingFMeasure() {
    Database db = makeSimpleDatabase(UNITTEST + "bisecting-test.csv", 300);
    KMeansBisecting<DoubleVector, MeanModel> kmeans = // 
    new ELKIBuilder<KMeansBisecting<DoubleVector, MeanModel>>(KMeansBisecting.class).with(KMeans.K_ID, // 
    2).with(KMeans.SEED_ID, // 
    0).with(BestOfMultipleKMeans.Parameterizer.TRIALS_ID, // 
    5).with(BestOfMultipleKMeans.Parameterizer.KMEANS_ID, // 
    KMeansLloyd.class).with(BestOfMultipleKMeans.Parameterizer.QUALITYMEASURE_ID, // 
    WithinClusterVarianceQualityMeasure.class).build();
    // run KMedians on database
    Clustering<MeanModel> result = kmeans.run(db);
    testFMeasure(db, result, 0.7408);
}

Example 7 with DoubleVector

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

the class KMeansElkanTest method testKMeansElkan.

/**
 * Run KMeans with fixed parameters and compare the result to a golden
 * standard.
 */
@Test
public void testKMeansElkan() {
    Database db = makeSimpleDatabase(UNITTEST + "different-densities-2d-no-noise.ascii", 1000);
    Clustering<?> result = // 
    new ELKIBuilder<KMeansElkan<DoubleVector>>(KMeansElkan.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 8 with DoubleVector

use of de.lmu.ifi.dbs.elki.data.DoubleVector 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 9 with DoubleVector

use of de.lmu.ifi.dbs.elki.data.DoubleVector 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 10 with DoubleVector

use of de.lmu.ifi.dbs.elki.data.DoubleVector 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 });
}