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diff --git a/src/de/lmu/ifi/dbs/elki/distance/distancefunction/set/HammingDistanceFunction.java b/src/de/lmu/ifi/dbs/elki/distance/distancefunction/set/HammingDistanceFunction.java
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+++ b/src/de/lmu/ifi/dbs/elki/distance/distancefunction/set/HammingDistanceFunction.java
@@ -0,0 +1,175 @@
+package de.lmu.ifi.dbs.elki.distance.distancefunction.set;
+
+/*
+ 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 de.lmu.ifi.dbs.elki.data.BitVector;
+import de.lmu.ifi.dbs.elki.data.FeatureVector;
+import de.lmu.ifi.dbs.elki.data.NumberVector;
+import de.lmu.ifi.dbs.elki.data.type.SimpleTypeInformation;
+import de.lmu.ifi.dbs.elki.data.type.TypeUtil;
+import de.lmu.ifi.dbs.elki.distance.distancefunction.NumberVectorDistanceFunction;
+import de.lmu.ifi.dbs.elki.utilities.documentation.Reference;
+import de.lmu.ifi.dbs.elki.utilities.optionhandling.AbstractParameterizer;
+
+/**
+ * Computes the Hamming distance of arbitrary vectors - i.e. counting, on how
+ * many places they differ.
+ * 
+ * Reference:
+ * <p>
+ * R. W. Hamming<br />
+ * Error detecting and error correcting codes<br />
+ * Bell System technical journal, 29(2)
+ * </p>
+ * 
+ * TODO: add a sparse (but not binary) optimized version?
+ * 
+ * @author Erich Schubert
+ */
+@Reference(authors = "R. W. Hamming", //
+title = "Error detecting and error correcting codes", //
+booktitle = "Bell System technical journal, 29(2)", //
+url = "http://dx.doi.org/10.1002/j.1538-7305.1950.tb00463.x")
+public class HammingDistanceFunction extends AbstractSetDistanceFunction<FeatureVector<?>> implements NumberVectorDistanceFunction<FeatureVector<?>> {
+  /**
+   * Static instance.
+   */
+  public static final HammingDistanceFunction STATIC = new HammingDistanceFunction();
+
+  @Override
+  public boolean isMetric() {
+    return true;
+  }
+
+  @Override
+  public double distance(FeatureVector<?> o1, FeatureVector<?> o2) {
+    if(o1 instanceof BitVector && o2 instanceof BitVector) {
+      return ((BitVector) o1).hammingDistance((BitVector) o2);
+    }
+    if(o1 instanceof NumberVector && o2 instanceof NumberVector) {
+      return hammingDistanceNumberVector((NumberVector) o1, (NumberVector) o2);
+    }
+    final int d1 = o1.getDimensionality(), d2 = o2.getDimensionality();
+    int differences = 0;
+    int d = 0;
+    for(; d < d1 && d < d2; d++) {
+      Object v1 = o1.getValue(d), v2 = o2.getValue(d);
+      final boolean n1 = isNull(v1), n2 = isNull(v2);
+      if(n1 && n2) {
+        continue;
+      }
+      if(v1 instanceof Double && Double.isNaN((Double) v1)) {
+        continue;
+      }
+      if(v2 instanceof Double && Double.isNaN((Double) v2)) {
+        continue;
+      }
+      // One must be set.
+      if(n1 || n2 || !v1.equals(v2)) {
+        ++differences;
+      }
+    }
+    for(; d < d1; d++) {
+      Object v1 = o1.getValue(d);
+      if(!isNull(v1)) {
+        if(v1 instanceof Double && Double.isNaN((Double) v1)) {
+          continue;
+        }
+        ++differences;
+      }
+    }
+    for(; d < d2; d++) {
+      Object v2 = o2.getValue(d);
+      if(!isNull(v2)) {
+        if(v2 instanceof Double && Double.isNaN((Double) v2)) {
+          continue;
+        }
+        ++differences;
+      }
+    }
+    return differences;
+  }
+
+  @Override
+  public double distance(NumberVector o1, NumberVector o2) {
+    if(o1 instanceof BitVector && o2 instanceof BitVector) {
+      return ((BitVector) o1).hammingDistance((BitVector) o2);
+    }
+    return hammingDistanceNumberVector(o1, o2);
+  }
+
+  /**
+   * Version for number vectors.
+   * 
+   * @param o1 First vector
+   * @param o2 Second vector
+   * @return hamming distance
+   */
+  private double hammingDistanceNumberVector(NumberVector o1, NumberVector o2) {
+    final int d1 = o1.getDimensionality(), d2 = o2.getDimensionality();
+    int differences = 0;
+    int d = 0;
+    for(; d < d1 && d < d2; d++) {
+      double v1 = o1.doubleValue(d), v2 = o2.doubleValue(d);
+      if(v1 != v1 || v2 != v2) { /* NaN */
+        continue;
+      }
+      if(v1 != v2) {
+        ++differences;
+      }
+    }
+    for(; d < d1; d++) {
+      double v1 = o1.doubleValue(d);
+      if(v1 != 0. && v1 == v1 /* not NaN */) {
+        ++differences;
+      }
+    }
+    for(; d < d2; d++) {
+      double v2 = o2.doubleValue(d);
+      if(v2 != 0. && v2 == v2 /* not NaN */) {
+        ++differences;
+      }
+    }
+    return differences;
+  }
+
+  @Override
+  public SimpleTypeInformation<? super FeatureVector<?>> getInputTypeRestriction() {
+    return TypeUtil.FEATURE_VECTORS;
+  }
+
+  /**
+   * Parameterization class.
+   * 
+   * @author Erich Schubert
+   * 
+   * @apiviz.exclude
+   */
+  public static class Parameterizer extends AbstractParameterizer {
+    @Override
+    protected HammingDistanceFunction makeInstance() {
+      return STATIC;
+    }
+  }
+}