nl.bioinf.roelen.thema11.classifier_tools.BoundaryClassifier.java Source code

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Here is the source code for nl.bioinf.roelen.thema11.classifier_tools.BoundaryClassifier.java

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/*
 * Copyright (C) 2014 roelen
 *
 * This program is free software: you can redistribute it and/or modify
 * it under the terms of the GNU 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 General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with this program.  If not, see <http://www.gnu.org/licenses/>.
 */

package nl.bioinf.roelen.thema11.classifier_tools;

import java.util.logging.Level;
import java.util.logging.Logger;
import weka.classifiers.Classifier;
import weka.classifiers.rules.OneR;
import weka.classifiers.rules.ZeroR;
import weka.classifiers.trees.J48;
import weka.core.Instances;
import weka.core.converters.ConverterUtils;

/**
 * class to write classifiers
 * @author roelen
 */
public class BoundaryClassifier {
    /**
     * method to build a classifier
     * @param fileLocation the arrf file our attributes are in
     * @param method the method to use for building our classifier
     * @return the classifier object that was built
     */
    public static Classifier build(String fileLocation, String method) {
        //init classifier object
        Classifier classifier;
        classifier = null;

        try {
            //get data
            ConverterUtils.DataSource source = new ConverterUtils.DataSource(fileLocation);
            //SET DATA AND OPTIONS
            Instances data = source.getDataSet();

            //remove the name and position entries, these are not important for classifying
            data.deleteAttributeAt(data.numAttributes() - 2);
            data.deleteAttributeAt(data.numAttributes() - 2);
            data.setClassIndex(data.numAttributes() - 1);

            //prepare data for classifying
            String[] options = new String[1];
            //unpruned
            options[0] = "-U"; // unpruned tree
            //see what method was given
            switch (method.toUpperCase()) {
            case "J48":
                //Build J48 classifier
                classifier = new J48(); // new instance of tree
                break;
            case "OneR":
                //Build OneR classifier
                classifier = new OneR();
                break;
            case "ZeroR":
                //build (useless) ZeroR classifier
                classifier = new ZeroR();
                break;
            default:
                //default is building OneR
                classifier = new OneR();
                break;
            }
            //set the options and build that thing
            classifier.setOptions(options); // set the options
            classifier.buildClassifier(data); // build classifier

        } catch (Exception ex) {
            Logger.getLogger(BoundaryClassifier.class.getName()).log(Level.SEVERE, null, ex);
        }
        return classifier;
    }
}