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package de.lmu.ifi.dbs.elki.datasource.filter.normalization;
/*
This file is part of ELKI:
Environment for Developing KDD-Applications Supported by Index-Structures
Copyright (C) 2012
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.math.statistics.distribution.NormalDistribution;
/**
* 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 <O> Object type
*
* @apiviz.uses NumberVector
*/
public class AttributeWiseErfNormalization<O extends NumberVector<?>> extends AbstractNormalization<O> {
/**
* Constructor.
*/
public AttributeWiseErfNormalization() {
super();
}
@Override
public O restore(O featureVector) {
throw new UnsupportedOperationException("Not implemented yet.");
}
@Override
protected O filterSingleObject(O 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 SimpleTypeInformation<? super O> getInputTypeRestriction() {
return TypeUtil.NUMBER_VECTOR_FIELD;
}
}
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