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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) 2012
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.ArrayList;
import java.util.List;
import de.lmu.ifi.dbs.elki.data.NumberVector;
import de.lmu.ifi.dbs.elki.database.ids.ArrayModifiableDBIDs;
import de.lmu.ifi.dbs.elki.database.ids.DBIDIter;
import de.lmu.ifi.dbs.elki.database.ids.DBIDUtil;
import de.lmu.ifi.dbs.elki.database.ids.DBIDs;
import de.lmu.ifi.dbs.elki.database.query.distance.DistanceQuery;
import de.lmu.ifi.dbs.elki.database.relation.Relation;
import de.lmu.ifi.dbs.elki.distance.distancefunction.PrimitiveDistanceFunction;
import de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer;
/**
* Initialize K-means by using the first k objects as initial means.
*
* @author Erich Schubert
*
* @param <V> Vector type
*/
public class FirstKInitialMeans<V> implements KMeansInitialization<V>, KMedoidsInitialization<V> {
/**
* Constructor.
*/
public FirstKInitialMeans() {
super();
}
@Override
public List<V> chooseInitialMeans(Relation<V> relation, int k, PrimitiveDistanceFunction<? super V, ?> distanceFunction) {
DBIDIter iter = relation.iterDBIDs();
List<V> means = new ArrayList<V>(k);
for(int i = 0; i < k && iter.valid(); i++, iter.advance()) {
means.add(relation.get(iter));
}
return means;
}
@Override
public DBIDs chooseInitialMedoids(int k, DistanceQuery<? super V, ?> distanceFunction) {
DBIDIter iter = distanceFunction.getRelation().iterDBIDs();
ArrayModifiableDBIDs means = DBIDUtil.newArray(k);
for(int i = 0; i < k && iter.valid(); i++, iter.advance()) {
means.add(iter);
}
return means;
}
/**
* Parameterization class.
*
* @author Erich Schubert
*
* @apiviz.exclude
*/
public static class Parameterizer<V extends NumberVector<V, ?>> extends AbstractParameterizer {
@Override
protected FirstKInitialMeans<V> makeInstance() {
return new FirstKInitialMeans<V>();
}
}
}
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