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package de.lmu.ifi.dbs.elki.algorithm.clustering.trivial;
/*
This file is part of ELKI:
Environment for Developing KDD-Applications Supported by Index-Structures
Copyright (C) 2011
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 de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm;
import de.lmu.ifi.dbs.elki.algorithm.clustering.ClusteringAlgorithm;
import de.lmu.ifi.dbs.elki.data.Cluster;
import de.lmu.ifi.dbs.elki.data.Clustering;
import de.lmu.ifi.dbs.elki.data.model.ClusterModel;
import de.lmu.ifi.dbs.elki.data.model.Model;
import de.lmu.ifi.dbs.elki.data.type.TypeInformation;
import de.lmu.ifi.dbs.elki.data.type.TypeUtil;
import de.lmu.ifi.dbs.elki.database.ids.DBIDs;
import de.lmu.ifi.dbs.elki.database.relation.Relation;
import de.lmu.ifi.dbs.elki.logging.Logging;
import de.lmu.ifi.dbs.elki.utilities.documentation.Description;
import de.lmu.ifi.dbs.elki.utilities.documentation.Title;
/**
* Trivial pseudo-clustering that just considers all points to be noise.
*
* Useful for evaluation and testing.
*
* @author Erich Schubert
*/
@Title("Trivial all-noise clustering")
@Description("Returns a 'trivial' clustering which just considers all points as noise points.")
public class TrivialAllNoise extends AbstractAlgorithm<Clustering<Model>> implements ClusteringAlgorithm<Clustering<Model>> {
/**
* The logger for this class.
*/
private static final Logging logger = Logging.getLogger(TrivialAllNoise.class);
/**
* Constructor, adhering to
* {@link de.lmu.ifi.dbs.elki.utilities.optionhandling.Parameterizable}
*/
public TrivialAllNoise() {
super();
}
public Clustering<Model> run(Relation<?> relation) {
final DBIDs ids = relation.getDBIDs();
Clustering<Model> result = new Clustering<Model>("All-in-noise trivial Clustering", "allinnoise-clustering");
Cluster<Model> c = new Cluster<Model>(ids, true, ClusterModel.CLUSTER);
result.addCluster(c);
return result;
}
@Override
public TypeInformation[] getInputTypeRestriction() {
return TypeUtil.array(TypeUtil.ANY);
}
@Override
protected Logging getLogger() {
return logger;
}
}
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