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package de.lmu.ifi.dbs.elki.evaluation.clustering.pairsegments;
/*
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 java.util.List;
import de.lmu.ifi.dbs.elki.data.Clustering;
import de.lmu.ifi.dbs.elki.evaluation.Evaluator;
import de.lmu.ifi.dbs.elki.result.Result;
import de.lmu.ifi.dbs.elki.result.ResultHierarchy;
import de.lmu.ifi.dbs.elki.result.ResultUtil;
import de.lmu.ifi.dbs.elki.utilities.documentation.Reference;
/**
* Evaluate clustering results by building segments for their pairs: shared
* pairs and differences.
*
* Reference:
* <p>
* Evaluation of Clusterings – Metrics and Visual Support<br />
* Elke Achtert, Sascha Goldhofer, Hans-Peter Kriegel, Erich Schubert, Arthur
* Zimek<br />
* In: Proc. 28th International Conference on Data Engineering (ICDE) 2012
* </p>
*
* @author Sascha Goldhofer
* @author Erich Schubert
* @since 0.5.0
*
* @apiviz.uses Clustering
* @apiviz.uses Segments
*/
@Reference(title = "Evaluation of Clusterings – Metrics and Visual Support", //
authors = "Elke Achtert, Sascha Goldhofer, Hans-Peter Kriegel, Erich Schubert, Arthur Zimek", //
booktitle = "Proc. 28th International Conference on Data Engineering (ICDE) 2012", //
url = "http://dx.doi.org/10.1109/ICDE.2012.128")
public class ClusterPairSegmentAnalysis implements Evaluator {
/**
* Constructor.
*/
public ClusterPairSegmentAnalysis() {
super();
}
/**
* Perform clusterings evaluation
*/
@Override
public void processNewResult(ResultHierarchy hier, Result result) {
// Get all new clusterings
// TODO: handle clusterings added later, too. Can we update the result?
List<Clustering<?>> clusterings = ResultUtil.getClusteringResults(result);
// Abort if not enough clusterings to compare
if(clusterings.size() < 2) {
return;
}
// create segments
Segments segments = new Segments(clusterings);
hier.add(result, segments);
}
}
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