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diff --git a/src/de/lmu/ifi/dbs/elki/datasource/filter/normalization/columnwise/AttributeWiseErfNormalization.java b/src/de/lmu/ifi/dbs/elki/datasource/filter/normalization/columnwise/AttributeWiseErfNormalization.java
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--- /dev/null
+++ b/src/de/lmu/ifi/dbs/elki/datasource/filter/normalization/columnwise/AttributeWiseErfNormalization.java
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+package de.lmu.ifi.dbs.elki.datasource.filter.normalization.columnwise;
+
+/*
+ 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.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.datasource.filter.normalization.AbstractNormalization;
+import de.lmu.ifi.dbs.elki.logging.Logging;
+import de.lmu.ifi.dbs.elki.math.statistics.distribution.NormalDistribution;
+import de.lmu.ifi.dbs.elki.utilities.Alias;
+
+/**
+ * Attribute-wise Normalization using the error function. This mostly makes
+ * sense when you have data that has been mean-variance normalized before.
+ * 
+ * @author Erich Schubert
+ * 
+ * @param <V> Object type
+ * 
+ * @apiviz.uses NumberVector
+ */
+@Alias({ "de.lmu.ifi.dbs.elki.datasource.filter.normalization.AttributeWiseErfNormalization"})
+public class AttributeWiseErfNormalization<V extends NumberVector> extends AbstractNormalization<V> {
+  /**
+   * Class logger.
+   */
+  private static final Logging LOG = Logging.getLogger(AttributeWiseErfNormalization.class);
+
+  /**
+   * Constructor.
+   */
+  public AttributeWiseErfNormalization() {
+    super();
+  }
+
+  @Override
+  protected V filterSingleObject(V obj) {
+    double[] val = new double[obj.getDimensionality()];
+    for(int i = 0; i < val.length; i++) {
+      val[i] = NormalDistribution.erf(obj.doubleValue(i));
+    }
+    return factory.newNumberVector(val);
+  }
+
+  @Override
+  protected Logging getLogger() {
+    return LOG;
+  }
+
+  @Override
+  protected SimpleTypeInformation<? super V> getInputTypeRestriction() {
+    return TypeUtil.NUMBER_VECTOR_FIELD;
+  }
+}