testclassifiers.java

常用机器学习算法,java编写源代码,内含常用分类算法,包括说明文档

/* Copyright (C) 2002 Univ. of Massachusetts Amherst, Computer Science Dept.
   This file is part of "MALLET" (MAchine Learning for LanguagE Toolkit).
   http://www.cs.umass.edu/~mccallum/mallet
   This software is provided under the terms of the Common Public License,
   version 1.0, as published by http://www.opensource.org.  For further
   information, see the file `LICENSE' included with this distribution. */




/** 
   @author Andrew McCallum <a href="mailto:[e-mail]">[e-mail]</a>
 */

package edu.umass.cs.mallet.base.classify.tests;

import edu.umass.cs.mallet.base.types.*;
import edu.umass.cs.mallet.base.classify.*;
import edu.umass.cs.mallet.base.pipe.*;
import edu.umass.cs.mallet.base.util.*;
//import edu.umass.cs.mallet.base.pipe.SerialPipe;
import edu.umass.cs.mallet.base.pipe.iterator.ArrayIterator;
import junit.framework.*;
import java.net.URI;

public class TestClassifiers extends TestCase
{
	public TestClassifiers (String name)
	{
		super (name);
	}

	private static Alphabet dictOfSize (int size)
	{
		Alphabet ret = new Alphabet ();
		for (int i = 0; i < size; i++)
			ret.lookupIndex ("feature"+i);
		return ret;
	}

	public void testRandomTrained ()
	{
		ClassifierTrainer[] trainers = new ClassifierTrainer[3];
		trainers[0] = new NaiveBayesTrainer();
		trainers[1] = new MaxEntTrainer();
		trainers[2] = new DecisionTreeTrainer();

		Alphabet fd = dictOfSize (3);
		String[] classNames = new String[] {"class0", "class1", "class2"};

		InstanceList ilist = new InstanceList (new Random(1), fd, classNames, 200);

		InstanceList lists[] = ilist.split (new java.util.Random(2), new double[] {.5, .5});
		//System.out.println ("Training set size = "+lists[0].size());
		//System.out.println ("Testing set size = "+lists[1].size());
		
		Classifier[] classifiers = new Classifier[trainers.length];
		for (int i = 0; i < trainers.length; i++)
			classifiers[i] = trainers[i].train (lists[0]);

		System.out.println ("Accuracy on training set:");
		for (int i = 0; i < trainers.length; i++)
			System.out.println (classifiers[i].getClass().getName()
													+ ": " + new Trial (classifiers[i], lists[0]).accuracy());

		System.out.println ("Accuracy on testing set:");
		for (int i = 0; i < trainers.length; i++)
			System.out.println (classifiers[i].getClass().getName()
													+ ": " + new Trial (classifiers[i], lists[1]).accuracy());
	}
	
	
	public static Test suite ()
	{
		return new TestSuite (TestClassifiers.class);
	}

	protected void setUp ()
	{
	}

	public static void main (String[] args)
	{
		junit.textui.TestRunner.run (suite());
	}
	
}