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Diffstat (limited to 'elki/src/test/java/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/KMeansElkanTest.java')
-rw-r--r-- | elki/src/test/java/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/KMeansElkanTest.java | 66 |
1 files changed, 66 insertions, 0 deletions
diff --git a/elki/src/test/java/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/KMeansElkanTest.java b/elki/src/test/java/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/KMeansElkanTest.java new file mode 100644 index 00000000..2d1cbe5a --- /dev/null +++ b/elki/src/test/java/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/KMeansElkanTest.java @@ -0,0 +1,66 @@ +package de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans; + +/* + This file is part of ELKI: + Environment for Developing KDD-Applications Supported by Index-Structures + + Copyright (C) 2015 + Ludwig-Maximilians-Universität München + Lehr- und Forschungseinheit für Datenbanksysteme + ELKI Development Team + + This program is free software: you can redistribute it and/or modify + it under the terms of the GNU Affero General Public License as published by + the Free Software Foundation, either version 3 of the License, or + (at your option) any later version. + + This program is distributed in the hope that it will be useful, + but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + GNU Affero General Public License for more details. + + You should have received a copy of the GNU Affero General Public License + along with this program. If not, see <http://www.gnu.org/licenses/>. + */ + +import org.junit.Test; + +import de.lmu.ifi.dbs.elki.JUnit4Test; +import de.lmu.ifi.dbs.elki.algorithm.AbstractSimpleAlgorithmTest; +import de.lmu.ifi.dbs.elki.data.Clustering; +import de.lmu.ifi.dbs.elki.data.DoubleVector; +import de.lmu.ifi.dbs.elki.database.Database; +import de.lmu.ifi.dbs.elki.utilities.ClassGenericsUtil; +import de.lmu.ifi.dbs.elki.utilities.optionhandling.ParameterException; +import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.ListParameterization; + +/** + * Regression test for Elkan k-means. + * + * @author Erich Schubert + * @since 0.4.0 + */ +public class KMeansElkanTest extends AbstractSimpleAlgorithmTest implements JUnit4Test { + /** + * Run KMeans with fixed parameters and compare the result to a golden + * standard. + * + * @throws ParameterException + */ + @Test + public void testKMeansElkan() { + Database db = makeSimpleDatabase(UNITTEST + "different-densities-2d-no-noise.ascii", 1000); + + // Setup algorithm + ListParameterization params = new ListParameterization(); + params.addParameter(KMeans.K_ID, 5); + params.addParameter(KMeans.SEED_ID, 2); + AbstractKMeans<DoubleVector, ?> kmeans = ClassGenericsUtil.parameterizeOrAbort(KMeansElkan.class, params); + testParameterizationOk(params); + + // run KMeans on database + Clustering<?> result = kmeans.run(db); + testFMeasure(db, result, 0.998005); + testClusterSizes(result, new int[] { 199, 200, 200, 200, 201 }); + } +}
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