estimatedcriteriontest.java

一个很好的LIBSVM的JAVA源码。对于要研究和改进SVM算法的学者。可以参考。来自数据挖掘工具YALE工具包。

/*
 *  YALE - Yet Another Learning Environment
 *  Copyright (C) 2001-2004
 *      Simon Fischer, Ralf Klinkenberg, Ingo Mierswa, 
 *          Katharina Morik, Oliver Ritthoff
 *      Artificial Intelligence Unit
 *      Computer Science Department
 *      University of Dortmund
 *      44221 Dortmund,  Germany
 *  email: [e-mail]
 *  web:   http://yale.cs.uni-dortmund.de/
 *
 *  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 2 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, write to the Free Software
 *  Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307
 *  USA.
 */
package edu.udo.cs.yale.operator.performance.test;

import edu.udo.cs.yale.operator.performance.*;

/** Tests {@link EstimatedPerformance}.
 *
 *  @version $Id: EstimatedCriterionTest.java,v 1.6 2004/08/27 11:57:43 ingomierswa Exp $
 */
public class EstimatedCriterionTest extends CriterionTestCase {

    private EstimatedPerformance performance10x08, performance20x04;
    
    public void setUp() throws Exception {
	super.setUp();
	performance10x08 = new EstimatedPerformance("test_performance", 0.8, 10, false);
	performance20x04 = new EstimatedPerformance("test_performance", 0.4, 20, false);
    }

    public void tearDown() throws Exception {
	performance10x08 = performance20x04 = null;
	super.tearDown();
    }

    /** Tests micro and makro average. Since makro average is implemented in 
     *  {@link PerformanceCriterion}, this does not have to be tested for measured
     *  performance criteria. */
    public void testAverage() {
	performance10x08.buildAverage(performance20x04);
	assertEquals("Wrong weighted average", 
		     (10*0.8 + 20*0.4) / (10+20),
		     performance10x08.getValue(), 
		     0.0000001);
	assertEquals("Wrong makro average", 
		     (0.8 + 0.4) / 2, 
		     performance10x08.getMakroAverage(), 
		     0.0000001);
    }

    public void testClone() {
	cloneTest("Clone of simple criterion", performance10x08);
	performance10x08.buildAverage(performance20x04);
	cloneTest("Clone of averaged criterion", performance10x08);
    }

}