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源代码id3java的简单介绍( 五 )

IT技术String


assertTrue(StudentDA.updateReborrowable(2,0,1,new Date()));
}
public static void main(String[] args) {
//junit.textui.TestRunner.run(TestStudentDA.class);
//System.out.println(new TestStudentDA("TestStudentDA").countTestCases());
testGetBorrowBookInfor();
}
}
/*
*@author ougaoyan ,date:2008-10-19
*/
package test;
import junit.framework.Test;
import junit.framework.TestSuite;
public class AllTests {
public static Test suite() {
TestSuite suite = new TestSuite("Test for test");
suite.addTestSuite(TestLibManagerDA.class);
suite.addTestSuite(TestBookDA.class);
suite.addTestSuite(TestCipDA.class);
suite.addTestSuite(TestStudentDA.class);
//suite.addTestSuite(TestLibManagerDA.class);
//$JUnit-END$
return suite;
}
}
求助 weka 的ID3算法java源码/*
*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., 675 Mass Ave, Cambridge, MA 02139, USA.
*/
/*
*Id3.java
*Copyright (C) 1999 University of Waikato, Hamilton, New Zealand
【源代码id3java的简单介绍】*
*/
package weka.classifiers.trees;
import weka.classifiers.Classifier;
import weka.classifiers.Sourcable;
import weka.core.Attribute;
import weka.core.Capabilities;
import weka.core.Instance;
import weka.core.Instances;
import weka.core.NoSupportForMissingValuesException;
import weka.core.RevisionUtils;
import weka.core.TechnicalInformation;
import weka.core.TechnicalInformationHandler;
import weka.core.Utils;
import weka.core.Capabilities.Capability;
import weka.core.TechnicalInformation.Field;
import weka.core.TechnicalInformation.Type;
import java.util.Enumeration;
/**
!-- globalinfo-start --
* Class for constructing an unpruned decision tree based on the ID3 algorithm. Can only deal with nominal attributes. No missing values allowed. Empty leaves may result in unclassified instances. For more information see: br/
* br/
* R. Quinlan (1986). Induction of decision trees. Machine Learning. 1(1):81-106.
* p/
!-- globalinfo-end --
*
!-- technical-bibtex-start --
* BibTeX:
* pre
* #64;article{Quinlan1986,
*author = {R. Quinlan},
*journal = {Machine Learning},
*number = {1},
*pages = {81-106},
*title = {Induction of decision trees},
*volume = {1},
*year = {1986}
* }
* /pre
* p/
!-- technical-bibtex-end --
*
!-- options-start --
* Valid options are: p/
*
* pre -D
*If set, classifier is run in debug mode and
*may output additional info to the console/pre
*
!-- options-end --
*
* @author Eibe Frank (eibe@cs.waikato.ac.nz)
* @version $Revision: 6404 $
*/
public class Id3
extends Classifier
implements TechnicalInformationHandler, Sourcable {
/** for serialization */
static final long serialVersionUID = -2693678647096322561L;
/** The node's successors. */
private Id3[] m_Successors;
/** Attribute used for splitting. */
private Attribute m_Attribute;
/** Class value if node is leaf. */

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