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diff --git a/src/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/initialization/KMeansInitialization.java b/src/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/initialization/KMeansInitialization.java
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+++ b/src/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/initialization/KMeansInitialization.java
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+package de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization;
+
+/*
+ This file is part of ELKI:
+ Environment for Developing KDD-Applications Supported by Index-Structures
+
+ Copyright (C) 2014
+ 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.NumberVector;
+import de.lmu.ifi.dbs.elki.database.Database;
+import de.lmu.ifi.dbs.elki.database.relation.Relation;
+import de.lmu.ifi.dbs.elki.distance.distancefunction.PrimitiveDistanceFunction;
+
+/**
+ * Interface for initializing K-Means
+ * 
+ * @author Erich Schubert
+ * 
+ * @apiviz.landmark
+ * 
+ * @param <V> Vector type
+ */
+public interface KMeansInitialization<V extends NumberVector> {
+  /**
+   * Choose initial means
+   * 
+   * @param database Database context
+   * @param relation Relation
+   * @param k Parameter k
+   * @param distanceFunction Distance function
+   * @param factory Factory for output vectors.
+   * @param <T> Input vector type
+   * @param <O> Output vector type
+   * @return List of chosen means for k-means
+   */
+  public abstract <T extends V, O extends NumberVector> List<O> chooseInitialMeans(Database database, Relation<T> relation, int k, PrimitiveDistanceFunction<? super T> distanceFunction, NumberVector.Factory<O> factory);
+}