classcmar_app10.java

多关联分类算法

/* -------------------------------------------------------------------------- */
/*                                                                            */
/*                   APRIORI-TFP CMAR (CLASSIFICATION BASED ON                */
/*                 MULTIPLE ASSOCIATION RULES) TCV APPLICATIONC               */
/*                                                                            */
/*                             Frans Coenen                                   */
/*                                                                            */
/*                          Monday 8 march 2004                               */
/*                                                                            */
/*                      Department of Computer Science                        */
/*                        The University of Liverpool                         */
/*                                                                            */
/* -------------------------------------------------------------------------- */

import java.io.*;

/* Ten Cross Validation Classification application using the CMAR 
(Classification based on Multiple Associate Rules) algorithm proposed by Wenmin 
Li, Jiawei Han and Jian Pei, but founded on Apriori-TFP.

Compile using:

javacClassCMAR_App10.java

Run using the java interpreter. Example:

java ClassCMAR_App10 -FpimaIndians.D42.N768.C2.num -N2

(-F filename, -N number of classifiers).              */

public class ClassCMAR_App10 {

    // ------------------- FIELDS ------------------------

    // None

    // ---------------- CONSTRUCTORS ---------------------

    // None

    // ------------------ METHODS ------------------------

    public static void main(String[] args) throws IOException {

	// Create instance of class ClassificationCMAR	
	AprioriTFP_CMAR newClassification = new AprioriTFP_CMAR(args);
				
	// Read data to be mined from file (method in AssocRuleMining class)
	newClassification.inputDataSet();
	newClassification.setNumRowsInInputSet();
	
	// Create tenths data sets (method in ClassificationAprioriT class)
	newClassification.createTenthsDataSets();
	
	// Mine data, produce T-tree and generate CRs
	double time1 = (double) System.currentTimeMillis();
	newClassification.commenceTCVwithOutput();
	newClassification.outputDuration(time1,
				(double) System.currentTimeMillis());
	
	// End
	System.exit(0);
	}
    }