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

63 строки
2,4 КиБ
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.linkage.CompleteLinkage;
import org.clueminer.clustering.aggl.linkage.SingleLinkage;
import org.clueminer.clustering.api.AgglomerativeClustering;
import org.clueminer.clustering.api.AlgParams;
import org.clueminer.clustering.api.ClusteringAlgorithm;
import org.clueminer.clustering.api.ClusteringFactory;
import org.clueminer.dataset.api.Dataset;
import org.clueminer.dataset.api.Instance;
import org.clueminer.utils.Props;
/**
* Execute single clustering
*
* @author Tomas Barton
* @param <E>
*/
public class ClusteringBenchmark<E extends Instance> {
public Container<E> cluster(Dataset<E> dataset, Props props) {
ClusteringFactory cf = ClusteringFactory.getInstance();
ClusteringAlgorithm algorithm = cf.getProvider(props.get(AlgParams.ALG));
return new Container(algorithm, dataset, props);
}
public Container<E> cluster(ClusteringAlgorithm algorithm, Dataset<E> dataset, Props props) {
return new Container(algorithm, dataset, props);
}
public Container<E> hclust(final AgglomerativeClustering algorithm, final Dataset<E> dataset, final String linkage) {
Props props = new Props();
props.put(AlgParams.LINKAGE, linkage);
final Container<E> runnable = new Container(algorithm, dataset, props);
return runnable;
}
public Container<E> singleLinkage(final AgglomerativeClustering algorithm, final Dataset<E> dataset) {
return hclust(algorithm, dataset, SingleLinkage.name);
}
public Container<E> completeLinkage(final AgglomerativeClustering algorithm, final Dataset<E> dataset) {
return hclust(algorithm, dataset, CompleteLinkage.name);
}
}