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diff --git a/src/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/initialization/RandomlyGeneratedInitialMeans.java b/src/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/initialization/RandomlyGeneratedInitialMeans.java
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+++ b/src/de/lmu/ifi/dbs/elki/algorithm/clustering/kmeans/initialization/RandomlyGeneratedInitialMeans.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.ArrayList;
+import java.util.List;
+import java.util.Random;
+
+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.database.relation.RelationUtil;
+import de.lmu.ifi.dbs.elki.distance.distancefunction.PrimitiveDistanceFunction;
+import de.lmu.ifi.dbs.elki.math.MathUtil;
+import de.lmu.ifi.dbs.elki.math.random.RandomFactory;
+
+/**
+ * Initialize k-means by generating random vectors (within the data sets value
+ * range).
+ * 
+ * @author Erich Schubert
+ */
+public class RandomlyGeneratedInitialMeans extends AbstractKMeansInitialization<NumberVector> {
+  /**
+   * Constructor.
+   * 
+   * @param rnd Random generator.
+   */
+  public RandomlyGeneratedInitialMeans(RandomFactory rnd) {
+    super(rnd);
+  }
+
+  @Override
+  public <T extends NumberVector, V extends NumberVector> List<V> chooseInitialMeans(Database database, Relation<T> relation, int k, PrimitiveDistanceFunction<? super T> distanceFunction, NumberVector.Factory<V> factory) {
+    final int dim = RelationUtil.dimensionality(relation);
+    double[][] minmax = RelationUtil.computeMinMax(relation);
+    double[] min = minmax[0], scale = minmax[1];
+    for(int d = 0; d < dim; d++) {
+      scale[d] = scale[d] - min[d];
+    }
+    List<V> means = new ArrayList<>(k);
+    final Random random = rnd.getSingleThreadedRandom();
+    for(int i = 0; i < k; i++) {
+      double[] r = MathUtil.randomDoubleArray(dim, random);
+      // Rescale
+      for(int d = 0; d < dim; d++) {
+        r[d] = min[d] + scale[d] * r[d];
+      }
+      means.add(factory.newNumberVector(r));
+    }
+    return means;
+  }
+
+  /**
+   * Parameterization class.
+   * 
+   * @author Erich Schubert
+   * 
+   * @apiviz.exclude
+   */
+  public static class Parameterizer extends AbstractKMeansInitialization.Parameterizer {
+    @Override
+    protected RandomlyGeneratedInitialMeans makeInstance() {
+      return new RandomlyGeneratedInitialMeans(rnd);
+    }
+  }
+}
+\ No newline at end of file