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diff --git a/src/de/lmu/ifi/dbs/elki/index/tree/metrical/mtreevariants/strategies/split/RandomSplit.java b/src/de/lmu/ifi/dbs/elki/index/tree/metrical/mtreevariants/strategies/split/RandomSplit.java
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+++ b/src/de/lmu/ifi/dbs/elki/index/tree/metrical/mtreevariants/strategies/split/RandomSplit.java
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+package de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.strategies.split;
+
+/*
+ This file is part of ELKI:
+ Environment for Developing KDD-Applications Supported by Index-Structures
+
+ Copyright (C) 2013
+ 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.Random;
+
+import de.lmu.ifi.dbs.elki.database.ids.DBID;
+import de.lmu.ifi.dbs.elki.distance.distancevalue.NumberDistance;
+import de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTree;
+import de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.AbstractMTreeNode;
+import de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.MTreeEntry;
+import de.lmu.ifi.dbs.elki.utilities.RandomFactory;
+import de.lmu.ifi.dbs.elki.utilities.documentation.Reference;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.OptionID;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameterization.Parameterization;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.parameters.RandomParameter;
+
+/**
+ * Encapsulates the required methods for a split of a node in an M-Tree. The
+ * routing objects are chosen according to the RANDOM strategy.
+ * 
+ * Note: only the routing objects are chosen at random, this is not a random
+ * assignment!
+ * 
+ * Reference:
+ * <p>
+ * P. Ciaccia, M. Patella, P. Zezula<br />
+ * M-tree: An Efficient Access Method for Similarity Search in Metric Spaces<br />
+ * In Proceedings of 23rd International Conference on Very Large Data Bases
+ * (VLDB'97), August 25-29, 1997, Athens, Greece
+ * </p>
+ * 
+ * @author Elke Achtert
+ * 
+ * @param <O> the type of DatabaseObject to be stored in the M-Tree
+ * @param <D> the type of Distance used in the M-Tree
+ * @param <N> the type of AbstractMTreeNode used in the M-Tree
+ * @param <E> the type of MetricalEntry used in the M-Tree
+ */
+@Reference(authors = "P. Ciaccia, M. Patella, P. Zezula", title = "M-tree: An Efficient Access Method for Similarity Search in Metric Spaces", booktitle = "VLDB'97, Proceedings of 23rd International Conference on Very Large Data Bases, August 25-29, 1997, Athens, Greece", url = "http://www.vldb.org/conf/1997/P426.PDF")
+public class RandomSplit<O, D extends NumberDistance<D, ?>, N extends AbstractMTreeNode<O, D, N, E>, E extends MTreeEntry> extends MTreeSplit<O, D, N, E> {
+  /**
+   * Random generator.
+   */
+  private Random random;
+
+  /**
+   * Creates a new split object.
+   */
+  public RandomSplit(RandomFactory rnd) {
+    super();
+    this.random = rnd.getRandom();
+  }
+
+  /**
+   * Selects two objects of the specified node to be promoted and stored into
+   * the parent node. The m-RAD strategy considers all possible pairs of objects
+   * and, after partitioning the set of entries, promotes the pair of objects
+   * for which the sum of covering radiuses is minimum.
+   * 
+   * @param tree Tree to use
+   * @param node the node to be split
+   */
+  @Override
+  public Assignments<E> split(AbstractMTree<O, D, N, E, ?> tree, N node) {
+    int pos1 = random.nextInt(node.getNumEntries());
+    int pos2 = random.nextInt(node.getNumEntries() - 1);
+    if (pos2 >= pos1) {
+      ++pos2;
+    }
+    DBID id1 = node.getEntry(pos1).getRoutingObjectID();
+    DBID id2 = node.getEntry(pos2).getRoutingObjectID();
+
+    return balancedPartition(tree, node, id1, id2);
+  }
+
+  /**
+   * Parameterization class.
+   * 
+   * @author Erich Schubert
+   * 
+   * @apiviz.exclude
+   * 
+   * @param <O> the type of DatabaseObject to be stored in the M-Tree
+   * @param <D> the type of Distance used in the M-Tree
+   * @param <N> the type of AbstractMTreeNode used in the M-Tree
+   * @param <E> the type of MetricalEntry used in the M-Tree
+   */
+  public static class Parameterizer<O, D extends NumberDistance<D, ?>, N extends AbstractMTreeNode<O, D, N, E>, E extends MTreeEntry> extends AbstractParameterizer {
+    /**
+     * Option ID for the random generator.
+     */
+    public static final OptionID RANDOM_ID = new OptionID("mtree.randomsplit.random", "Random generator / seed for the randomized split.");
+
+    /**
+     * Random generator
+     */
+    RandomFactory rnd = RandomFactory.DEFAULT;
+
+    @Override
+    protected void makeOptions(Parameterization config) {
+      super.makeOptions(config);
+      RandomParameter rndP = new RandomParameter(RANDOM_ID);
+      if (config.grab(rndP)) {
+        rnd = rndP.getValue();
+      }
+    }
+
+    @Override
+    protected RandomSplit<O, D, N, E> makeInstance() {
+      return new RandomSplit<>(rnd);
+    }
+  }
+}