tutorials.tools.TutorialWekaClassifier.java Source code

Introduction

Here is the source code for tutorials.tools.TutorialWekaClassifier.java

Source

/**
 * This file is part of the Java Machine Learning Library
 * 
 * The Java Machine Learning Library 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 2 of the License, or
 * (at your option) any later version.
 * 
 * The Java Machine Learning Library 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 the Java Machine Learning Library; if not, write to the Free Software
 * Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA  02110-1301  USA
 * 
 * Copyright (c) 2006-2010, Thomas Abeel
 * 
 * Project: http://java-ml.sourceforge.net/
 * 
 */
package tutorials.tools;

import java.io.File;
import java.util.Map;

import net.sf.javaml.classification.Classifier;
import net.sf.javaml.classification.evaluation.CrossValidation;
import net.sf.javaml.classification.evaluation.PerformanceMeasure;
import net.sf.javaml.core.Dataset;
import net.sf.javaml.tools.data.FileHandler;
import net.sf.javaml.tools.weka.WekaClassifier;
import weka.classifiers.functions.SMO;

/**
 * Tutorial how to use a Weka classifier in Java-ML.
 * 
 * @author Thomas Abeel
 * 
 */
public class TutorialWekaClassifier {

    public static void main(String[] args) throws Exception {
        /* Load data */
        Dataset data = FileHandler.loadDataset(new File("devtools/data/iris.data"), 4, ",");
        /* Create Weka classifier */
        SMO smo = new SMO();
        /* Wrap Weka classifier in bridge */
        Classifier javamlsmo = new WekaClassifier(smo);
        /* Initialize cross-validation */
        CrossValidation cv = new CrossValidation(javamlsmo);
        /* Perform cross-validation */
        Map<Object, PerformanceMeasure> pm = cv.crossValidation(data);
        /* Output results */
        System.out.println(pm);
    }
}