use of de.lmu.ifi.dbs.elki.data.DoubleVector in project elki by elki-project.
the class EMTest method testEMMAPTextbook.
@Test
public void testEMMAPTextbook() {
Database db = makeSimpleDatabase(UNITTEST + "hierarchical-2d.ascii", 710);
Clustering<?> result = //
new ELKIBuilder<EM<DoubleVector, ?>>(EM.class).with(KMeans.SEED_ID, //
0).with(EM.Parameterizer.PRIOR_ID, //
10).with(EM.Parameterizer.K_ID, //
5).with(EM.Parameterizer.INIT_ID, //
TextbookMultivariateGaussianModelFactory.class).build().run(db);
testFMeasure(db, result, 0.958843);
testClusterSizes(result, new int[] { 3, 95, 97, 202, 313 });
}
use of de.lmu.ifi.dbs.elki.data.DoubleVector in project elki by elki-project.
the class EMTest method testEMMAPTwoPass.
@Test
public void testEMMAPTwoPass() {
Database db = makeSimpleDatabase(UNITTEST + "hierarchical-2d.ascii", 710);
Clustering<?> result = //
new ELKIBuilder<EM<DoubleVector, ?>>(EM.class).with(KMeans.SEED_ID, //
0).with(EM.Parameterizer.PRIOR_ID, //
10).with(EM.Parameterizer.K_ID, //
5).with(EM.Parameterizer.INIT_ID, //
TwoPassMultivariateGaussianModelFactory.class).build().run(db);
testFMeasure(db, result, 0.958843);
testClusterSizes(result, new int[] { 3, 95, 97, 202, 313 });
}
use of de.lmu.ifi.dbs.elki.data.DoubleVector in project elki by elki-project.
the class EMTest method testEMMAPSpherical.
@Test
public void testEMMAPSpherical() {
Database db = makeSimpleDatabase(UNITTEST + "hierarchical-2d.ascii", 710);
Clustering<?> result = //
new ELKIBuilder<EM<DoubleVector, ?>>(EM.class).with(KMeans.SEED_ID, //
1).with(EM.Parameterizer.K_ID, //
4).with(EM.Parameterizer.INIT_ID, //
SphericalGaussianModelFactory.class).with(EM.Parameterizer.PRIOR_ID, //
10).build().run(db);
testFMeasure(db, result, 0.9357286);
testClusterSizes(result, new int[] { 103, 104, 208, 295 });
}
use of de.lmu.ifi.dbs.elki.data.DoubleVector in project elki by elki-project.
the class LSDBCTest method testLSDBCOnSingleLinkDataset.
@Test
public void testLSDBCOnSingleLinkDataset() {
Database db = makeSimpleDatabase(UNITTEST + "single-link-effect.ascii", 638);
Clustering<Model> result = //
new ELKIBuilder<LSDBC<DoubleVector>>(LSDBC.class).with(LSDBC.Parameterizer.ALPHA_ID, //
0.2).with(LSDBC.Parameterizer.K_ID, //
120).build().run(db);
testFMeasure(db, result, 0.95681073);
testClusterSizes(result, new int[] { 32, 197, 203, 206 });
}
use of de.lmu.ifi.dbs.elki.data.DoubleVector in project elki by elki-project.
the class FourCTest method testFourCOverlap.
/**
* Run 4C with fixed parameters and compare the result to a golden standard.
*/
@Test
public void testFourCOverlap() {
Database db = makeSimpleDatabase(UNITTEST + "correlation-overlap-3-5d.ascii", 650);
Clustering<Model> result = //
new ELKIBuilder<FourC<DoubleVector>>(FourC.class).with(DBSCAN.Parameterizer.EPSILON_ID, //
3).with(DBSCAN.Parameterizer.MINPTS_ID, //
50).with(LimitEigenPairFilter.Parameterizer.EIGENPAIR_FILTER_DELTA, //
0.5).with(FourC.Settings.Parameterizer.LAMBDA_ID, //
3).build().run(db);
testFMeasure(db, result, 0.9073744);
testClusterSizes(result, new int[] { 200, 202, 248 });
}
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