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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 de.lmu.ifi.dbs.elki.database.ids.DBIDs;
+import de.lmu.ifi.dbs.elki.database.query.distance.DistanceQuery;
+
+/**
+ * Interface for initializing K-Medoids. In contrast to k-means initializers,
+ * this initialization will only return members of the original data set.
+ *
+ * @author Erich Schubert
+ *
+ * @param <V> Object type
+ */
+public interface KMedoidsInitialization<V> {
+ /**
+ * Choose initial means
+ *
+ * @param k Parameter k
+ * @param distanceFunction Distance function
+ * @return List of chosen means for k-means
+ */
+ public abstract DBIDs chooseInitialMedoids(int k, DistanceQuery<? super V, ?> distanceFunction);
+} \ No newline at end of file