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tp-apprentissage/clustering-benchmark-master/src/test/java/org/clueminer/clustering/benchmark/HclustBenchmarkTest.java
Titouan Labourdette e3009c62af 1er commit
2021-09-28 15:35:45 +02:00

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Java

/*
* Copyright (C) 2011-2016 clueminer.org
*
* This program is free software: you can redistribute it and/or modify
* it under the terms of the GNU 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 General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
package org.clueminer.clustering.benchmark;
import org.clueminer.clustering.aggl.HC;
import org.clueminer.clustering.aggl.HCLW;
import org.clueminer.clustering.aggl.linkage.AverageLinkage;
import org.clueminer.clustering.aggl.linkage.MedianLinkage;
import org.clueminer.clustering.aggl.linkage.SingleLinkage;
import org.clueminer.clustering.api.AgglomerativeClustering;
import org.clueminer.dataset.api.Dataset;
import org.clueminer.dataset.api.Instance;
import org.clueminer.fixtures.clustering.FakeDatasets;
import org.clueminer.report.NanoBench;
import static org.junit.Assert.assertEquals;
import org.junit.Test;
/**
*
* @author deric
*/
public class HclustBenchmarkTest {
private final AgglomerativeClustering[] algorithms;
public HclustBenchmarkTest() {
//algorithms = new AgglomerativeClustering[]{new HAC(), new HACLW(), new HCL(), new HACLWMS()};
algorithms = new AgglomerativeClustering[]{new HC(), new HCLW()};
}
@Test
public void testSingleLinkage() {
Dataset<? extends Instance> dataset = FakeDatasets.irisDataset();
for (AgglomerativeClustering alg : algorithms) {
NanoBench.create().measurements(2).cpuAndMemory().measure(
alg.getName() + " single link - " + dataset.getName(),
new ClusteringBenchmark().singleLinkage(alg, dataset)
);
}
}
@Test
public void testCompleteLinkage() {
Dataset<? extends Instance> dataset = FakeDatasets.irisDataset();
for (AgglomerativeClustering alg : algorithms) {
NanoBench.create().cpuAndMemory().measurements(2).measure(
alg.getName() + " complete link - " + dataset.getName(),
new ClusteringBenchmark().completeLinkage(alg, dataset)
);
}
}
@Test
public void testSingleLinkageSameResultTwoAlg() {
//Dataset<? extends Instance> dataset = FakeDatasets.schoolData();
Dataset<? extends Instance> dataset = FakeDatasets.kumarData();
//use one algorithm as reference one
AgglomerativeClustering alg1 = new HC();
Container ref = new ClusteringBenchmark().completeLinkage(alg1, dataset);
ref.run();
Container other;
AgglomerativeClustering alg2 = new HCLW();
other = new ClusteringBenchmark().completeLinkage(alg2, dataset);
other.run();
System.out.println("comparing " + algorithms[0].getName() + " vs " + alg2.getName());
assertEquals(true, ref.equals(other));
}
/**
* TODO: single linkage gives different results
*/
//@Test
public void testSingleLinkageSameResult() {
//Dataset<? extends Instance> dataset = FakeDatasets.schoolData();
Dataset<? extends Instance> dataset = FakeDatasets.kumarData();
String linkage = SingleLinkage.name;
compareTreeResults(dataset, linkage, algorithms);
}
@Test
public void testAverageLinkageResult() {
String linkage = AverageLinkage.name;
Dataset<? extends Instance> dataset = FakeDatasets.schoolData();
compareTreeResults(dataset, linkage, algorithms);
}
/**
* TODO: median (centroid) linkage is broken
*/
//@Test
public void testMedianLinkageResult() {
String linkage = MedianLinkage.name;
Dataset<? extends Instance> dataset = FakeDatasets.schoolData();
compareTreeResults(dataset, linkage, new AgglomerativeClustering[]{new HC(), new HCLW()});
}
private void compareTreeResults(Dataset<? extends Instance> dataset, String linkage, AgglomerativeClustering[] algs) {
//use one algorithm as reference one
Container ref = new ClusteringBenchmark().hclust(algs[0], dataset, linkage);
ref.run();
Container other;
//compare result to others
for (int i = 1; i < algs.length; i++) {
AgglomerativeClustering algorithm = algs[i];
other = new ClusteringBenchmark().hclust(algorithm, dataset, linkage);
other.run();
System.out.println("comparing " + algs[0].getName() + " vs " + algorithm.getName() + " linkage: " + linkage);
assertEquals(true, ref.equals(other));
}
}
}