source: trunk/CrossPare/src/de/ugoe/cs/cpdp/dataprocessing/Normalization.java @ 50

// Copyright 2015 Georg-August-Universität Göttingen, Germany
//
//   Licensed under the Apache License, Version 2.0 (the "License");
//   you may not use this file except in compliance with the License.
//   You may obtain a copy of the License at
//
//       http://www.apache.org/licenses/LICENSE-2.0
//
//   Unless required by applicable law or agreed to in writing, software
//   distributed under the License is distributed on an "AS IS" BASIS,
//   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
//   See the License for the specific language governing permissions and
//   limitations under the License.

package de.ugoe.cs.cpdp.dataprocessing;

import org.apache.commons.collections4.list.SetUniqueList;

import weka.core.Attribute;
import weka.core.Instance;
import weka.core.Instances;
import weka.experiment.Stats;

/**
 * Normalizes each attribute of each data set separately.
 * 
 * @author Steffen Herbold
 */
public class Normalization implements ISetWiseProcessingStrategy, IProcessesingStrategy {

    /**
     * @see de.ugoe.cs.cpdp.dataprocessing.SetWiseProcessingStrategy#apply(weka.core.Instances,
     *      org.apache.commons.collections4.list.SetUniqueList)
     */
    @Override
    public void apply(Instances testdata, SetUniqueList<Instances> traindataSet) {
        final Attribute classAtt = testdata.classAttribute();

        for (int i = 0; i < testdata.numAttributes(); i++) {
            if (!testdata.attribute(i).equals(classAtt)) {
                Stats teststats = testdata.attributeStats(i).numericStats;

                double minVal = teststats.min;
                double maxVal = teststats.max;

                for (Instances traindata : traindataSet) {
                    Stats trainstats = traindata.attributeStats(i).numericStats;
                    if (minVal > trainstats.min) {
                        minVal = trainstats.min;
                    }
                    if (maxVal < trainstats.max) {
                        maxVal = trainstats.max;
                    }
                }

                for (int j = 0; j < testdata.numInstances(); j++) {
                    Instance inst = testdata.instance(j);
                    double newValue = (inst.value(i) - minVal) / (maxVal - minVal);
                    inst.setValue(i, newValue);
                }

                for (Instances traindata : traindataSet) {
                    for (int j = 0; j < traindata.numInstances(); j++) {
                        Instance inst = traindata.instance(j);
                        double newValue = (inst.value(i) - minVal) / (maxVal - minVal);
                        inst.setValue(i, newValue);
                    }
                }
            }
        }

    }

    /**
     * @see de.ugoe.cs.cpdp.dataprocessing.ProcessesingStrategy#apply(weka.core.Instances,
     *      weka.core.Instances)
     */
    @Override
    public void apply(Instances testdata, Instances traindata) {
        final Attribute classAtt = testdata.classAttribute();

        for (int i = 0; i < testdata.numAttributes(); i++) {
            if (!testdata.attribute(i).equals(classAtt)) {
                Stats teststats = testdata.attributeStats(i).numericStats;

                double minVal = teststats.min;
                double maxVal = teststats.max;

                Stats trainstats = traindata.attributeStats(i).numericStats;
                if (minVal > trainstats.min) {
                    minVal = trainstats.min;
                }
                if (maxVal < trainstats.max) {
                    maxVal = trainstats.max;
                }

                for (int j = 0; j < testdata.numInstances(); j++) {
                    Instance inst = testdata.instance(j);
                    double newValue = (inst.value(i) - minVal) / (maxVal - minVal);
                    inst.setValue(i, newValue);
                }

                for (int j = 0; j < traindata.numInstances(); j++) {
                    Instance inst = traindata.instance(j);
                    double newValue = (inst.value(i) - minVal) / (maxVal - minVal);
                    inst.setValue(i, newValue);
                }
            }
        }
    }

    /**
     * Does not have parameters. String is ignored.
     * 
     * @param parameters
     *            ignored
     */
    @Override
    public void setParameter(String parameters) {
        // no parameters
    }
}