Java tutorial
/* * AgrawalGenerator.java * Copyright (C) 2007 University of Waikato, Hamilton, New Zealand * @author Richard Kirkby (rkirkby@cs.waikato.ac.nz) * * 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. */ package tr.gov.ulakbim.jDenetX.streams.generators; import tr.gov.ulakbim.jDenetX.core.InstancesHeader; import tr.gov.ulakbim.jDenetX.core.ObjectRepository; import tr.gov.ulakbim.jDenetX.options.AbstractOptionHandler; import tr.gov.ulakbim.jDenetX.options.FlagOption; import tr.gov.ulakbim.jDenetX.options.FloatOption; import tr.gov.ulakbim.jDenetX.options.IntOption; import tr.gov.ulakbim.jDenetX.streams.InstanceStream; import tr.gov.ulakbim.jDenetX.tasks.TaskMonitor; import weka.core.*; import java.util.Random; // Generator described in paper: // Rakesh Agrawal, Tomasz Imielinksi, and Arun Swami, // "Database Mining: A Performance Perspective", // IEEE Transactions on Knowledge and Data Engineering, // 5(6), December 1993. // Public C source code available at: // http://www.almaden.ibm.com/cs/projects/iis/hdb/Projects/data_mining/datasets/syndata.html // // Notes: // The built in functions are based on the paper (page 924), // which turn out to be functions pred20 thru pred29 in the public C implementation // Perturbation function works like C implementation rather than description in paper public class AgrawalGenerator extends AbstractOptionHandler implements InstanceStream { @Override public String getPurposeString() { return "Generates one of ten different pre-defined loan functions."; } private static final long serialVersionUID = 1L; public IntOption functionOption = new IntOption("function", 'f', "Classification function used, as defined in the original paper.", 1, 1, 10); public IntOption instanceRandomSeedOption = new IntOption("instanceRandomSeed", 'i', "Seed for random generation of instances.", 1); public FloatOption peturbFractionOption = new FloatOption("peturbFraction", 'p', "The amount of peturbation (noise) introduced to numeric values.", 0.05, 0.0, 1.0); public FlagOption balanceClassesOption = new FlagOption("balanceClasses", 'b', "Balance the number of instances of each class."); protected interface ClassFunction { public int determineClass(double salary, double commission, int age, int elevel, int car, int zipcode, double hvalue, int hyears, double loan); } protected static ClassFunction[] classificationFunctions = { // function 1 new ClassFunction() { public int determineClass(double salary, double commission, int age, int elevel, int car, int zipcode, double hvalue, int hyears, double loan) { return ((age < 40) || (60 <= age)) ? 0 : 1; } }, // function 2 new ClassFunction() { public int determineClass(double salary, double commission, int age, int elevel, int car, int zipcode, double hvalue, int hyears, double loan) { if (age < 40) { return ((50000 <= salary) && (salary <= 100000)) ? 0 : 1; } else if (age < 60) {// && age >= 40 return ((75000 <= salary) && (salary <= 125000)) ? 0 : 1; } else {// age >= 60 return ((25000 <= salary) && (salary <= 75000)) ? 0 : 1; } } }, // function 3 new ClassFunction() { public int determineClass(double salary, double commission, int age, int elevel, int car, int zipcode, double hvalue, int hyears, double loan) { if (age < 40) { return ((elevel == 0) || (elevel == 1)) ? 0 : 1; } else if (age < 60) { // && age >= 40 return ((elevel == 1) || (elevel == 2) || (elevel == 3)) ? 0 : 1; } else { // age >= 60 return ((elevel == 2) || (elevel == 3) || (elevel == 4)) ? 0 : 1; } } }, // function 4 new ClassFunction() { public int determineClass(double salary, double commission, int age, int elevel, int car, int zipcode, double hvalue, int hyears, double loan) { if (age < 40) { if ((elevel == 0) || (elevel == 1)) { return ((25000 <= salary) && (salary <= 75000)) ? 0 : 1; } return ((50000 <= salary) && (salary <= 100000)) ? 0 : 1; } else if (age < 60) {// && age >= 40 if ((elevel == 1) || (elevel == 2) || (elevel == 3)) { return ((50000 <= salary) && (salary <= 100000)) ? 0 : 1; } return ((75000 <= salary) && (salary <= 125000)) ? 0 : 1; } else {// age >= 60 if ((elevel == 2) || (elevel == 3) || (elevel == 4)) { return ((50000 <= salary) && (salary <= 100000)) ? 0 : 1; } return ((25000 <= salary) && (salary <= 75000)) ? 0 : 1; } } }, // function 5 new ClassFunction() { public int determineClass(double salary, double commission, int age, int elevel, int car, int zipcode, double hvalue, int hyears, double loan) { if (age < 40) { if ((50000 <= salary) && (salary <= 100000)) { return ((100000 <= loan) && (loan <= 300000)) ? 0 : 1; } return ((200000 <= loan) && (loan <= 400000)) ? 0 : 1; } else if (age < 60) {// && age >= 40 if ((75000 <= salary) && (salary <= 125000)) { return ((200000 <= loan) && (loan <= 400000)) ? 0 : 1; } return ((300000 <= loan) && (loan <= 500000)) ? 0 : 1; } else {// age >= 60 if ((25000 <= salary) && (salary <= 75000)) { return ((300000 <= loan) && (loan <= 500000)) ? 0 : 1; } return ((100000 <= loan) && (loan <= 300000)) ? 0 : 1; } } }, // function 6 new ClassFunction() { public int determineClass(double salary, double commission, int age, int elevel, int car, int zipcode, double hvalue, int hyears, double loan) { double totalSalary = salary + commission; if (age < 40) { return ((50000 <= totalSalary) && (totalSalary <= 100000)) ? 0 : 1; } else if (age < 60) {// && age >= 40 return ((75000 <= totalSalary) && (totalSalary <= 125000)) ? 0 : 1; } else {// age >= 60 return ((25000 <= totalSalary) && (totalSalary <= 75000)) ? 0 : 1; } } }, // function 7 new ClassFunction() { public int determineClass(double salary, double commission, int age, int elevel, int car, int zipcode, double hvalue, int hyears, double loan) { double disposable = (2.0 * (salary + commission) / 3.0 - loan / 5.0 - 20000.0); return disposable > 0 ? 0 : 1; } }, // function 8 new ClassFunction() { public int determineClass(double salary, double commission, int age, int elevel, int car, int zipcode, double hvalue, int hyears, double loan) { double disposable = (2.0 * (salary + commission) / 3.0 - 5000.0 * elevel - 20000.0); return disposable > 0 ? 0 : 1; } }, // function 9 new ClassFunction() { public int determineClass(double salary, double commission, int age, int elevel, int car, int zipcode, double hvalue, int hyears, double loan) { double disposable = (2.0 * (salary + commission) / 3.0 - 5000.0 * elevel - loan / 5.0 - 10000.0); return disposable > 0 ? 0 : 1; } }, // function 10 new ClassFunction() { public int determineClass(double salary, double commission, int age, int elevel, int car, int zipcode, double hvalue, int hyears, double loan) { double equity = 0.0; if (hyears >= 20) { equity = hvalue * (hyears - 20.0) / 10.0; } double disposable = (2.0 * (salary + commission) / 3.0 - 5000.0 * elevel + equity / 5.0 - 10000.0); return disposable > 0 ? 0 : 1; } } }; protected InstancesHeader streamHeader; protected Random instanceRandom; protected boolean nextClassShouldBeZero; @Override protected void prepareForUseImpl(TaskMonitor monitor, ObjectRepository repository) { // generate header FastVector attributes = new FastVector(); attributes.addElement(new Attribute("salary")); attributes.addElement(new Attribute("commission")); attributes.addElement(new Attribute("age")); FastVector elevelLabels = new FastVector(); for (int i = 0; i < 5; i++) { elevelLabels.addElement("level" + i); } attributes.addElement(new Attribute("elevel", elevelLabels)); FastVector carLabels = new FastVector(); for (int i = 0; i < 20; i++) { carLabels.addElement("car" + (i + 1)); } attributes.addElement(new Attribute("car", carLabels)); FastVector zipCodeLabels = new FastVector(); for (int i = 0; i < 9; i++) { zipCodeLabels.addElement("zipcode" + (i + 1)); } attributes.addElement(new Attribute("zipcode", zipCodeLabels)); attributes.addElement(new Attribute("hvalue")); attributes.addElement(new Attribute("hyears")); attributes.addElement(new Attribute("loan")); FastVector classLabels = new FastVector(); classLabels.addElement("groupA"); classLabels.addElement("groupB"); attributes.addElement(new Attribute("class", classLabels)); this.streamHeader = new InstancesHeader( new Instances(getCLICreationString(InstanceStream.class), attributes, 0)); this.streamHeader.setClassIndex(this.streamHeader.numAttributes() - 1); restart(); } public long estimatedRemainingInstances() { return -1; } public InstancesHeader getHeader() { return this.streamHeader; } public boolean hasMoreInstances() { return true; } public boolean isRestartable() { return true; } public Instance nextInstance() { double salary = 0, commission = 0, hvalue = 0, loan = 0; int age = 0, elevel = 0, car = 0, zipcode = 0, hyears = 0, group = 0; boolean desiredClassFound = false; while (!desiredClassFound) { // generate attributes salary = 20000.0 + 130000.0 * this.instanceRandom.nextDouble(); commission = (salary >= 75000.0) ? 0 : (10000.0 + 65000.0 * this.instanceRandom.nextDouble()); // true to c implementation: // if (instanceRandom.nextDouble() < 0.5 && salary < 75000.0) // commission = 10000.0 + 65000.0 * instanceRandom.nextDouble(); age = 20 + this.instanceRandom.nextInt(61); elevel = this.instanceRandom.nextInt(5); car = this.instanceRandom.nextInt(20); zipcode = this.instanceRandom.nextInt(9); hvalue = (9.0 - zipcode) * 100000.0 * (0.5 + this.instanceRandom.nextDouble()); hyears = 1 + this.instanceRandom.nextInt(30); loan = this.instanceRandom.nextDouble() * 500000.0; // determine class group = classificationFunctions[this.functionOption.getValue() - 1].determineClass(salary, commission, age, elevel, car, zipcode, hvalue, hyears, loan); if (!this.balanceClassesOption.isSet()) { desiredClassFound = true; } else { // balance the classes if ((this.nextClassShouldBeZero && (group == 0)) || (!this.nextClassShouldBeZero && (group == 1))) { desiredClassFound = true; this.nextClassShouldBeZero = !this.nextClassShouldBeZero; } // else keep searching } } // perturb values if (this.peturbFractionOption.getValue() > 0.0) { salary = perturbValue(salary, 20000, 150000); if (commission > 0) { commission = perturbValue(commission, 10000, 75000); } age = (int) Math.round(perturbValue(age, 20, 80)); hvalue = perturbValue(hvalue, (9.0 - zipcode) * 100000.0, 0, 135000); hyears = (int) Math.round(perturbValue(hyears, 1, 30)); loan = perturbValue(loan, 0, 500000); } // construct instance InstancesHeader header = getHeader(); Instance inst = new DenseInstance(header.numAttributes()); inst.setValue(0, salary); inst.setValue(1, commission); inst.setValue(2, age); inst.setValue(3, elevel); inst.setValue(4, car); inst.setValue(5, zipcode); inst.setValue(6, hvalue); inst.setValue(7, hyears); inst.setValue(8, loan); inst.setDataset(header); inst.setClassValue(group); return inst; } protected double perturbValue(double val, double min, double max) { return perturbValue(val, max - min, min, max); } protected double perturbValue(double val, double range, double min, double max) { val += range * (2.0 * (this.instanceRandom.nextDouble() - 0.5)) * this.peturbFractionOption.getValue(); if (val < min) { val = min; } else if (val > max) { val = max; } return val; } public void restart() { this.instanceRandom = new Random(this.instanceRandomSeedOption.getValue()); this.nextClassShouldBeZero = false; } public void getDescription(StringBuilder sb, int indent) { // TODO Auto-generated method stub } }