agrawal.java

代码是一个分类器的实现,其中使用了部分weka的源代码。可以将项目导入eclipse运行

/*
 *    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.
 */

/*
 * Agrawal.java
 * Copyright (C) 2005 University of Waikato, Hamilton, New Zealand
 *
 */

package weka.datagenerators.classifiers.classification;

import weka.core.Attribute;
import weka.core.FastVector;
import weka.core.Instance;
import weka.core.Instances;
import weka.core.Option;
import weka.core.SelectedTag;
import weka.core.Tag;
import weka.core.TechnicalInformation;
import weka.core.TechnicalInformationHandler;
import weka.core.Utils;
import weka.core.TechnicalInformation.Field;
import weka.core.TechnicalInformation.Type;
import weka.datagenerators.ClassificationGenerator;

import java.util.Enumeration;
import java.util.Random;
import java.util.Vector;

/**
 <!-- globalinfo-start -->
 * Generates a people database and is based on the paper by Agrawal et al.:<br/>
 * R. Agrawal, T. Imielinski, A. Swami (1993). Database Mining: A Performance Perspective. IEEE Transactions on Knowledge and Data Engineering. 5(6):914-925. URL http://www.almaden.ibm.com/software/quest/Publications/ByDate.html.
 * <p/>
 <!-- globalinfo-end -->
 *
 <!-- technical-bibtex-start -->
 * BibTeX:
 * <pre>
 * &#64;article{Agrawal1993,
 *    author = {R. Agrawal and T. Imielinski and A. Swami},
 *    journal = {IEEE Transactions on Knowledge and Data Engineering},
 *    note = {Special issue on Learning and Discovery in Knowledge-Based Databases},
 *    number = {6},
 *    pages = {914-925},
 *    title = {Database Mining: A Performance Perspective},
 *    volume = {5},
 *    year = {1993},
 *    URL = {http://www.almaden.ibm.com/software/quest/Publications/ByDate.html},
 *    PDF = {http://www.almaden.ibm.com/software/quest/Publications/papers/tkde93.pdf}
 * }
 * </pre>
 * <p/>
 <!-- technical-bibtex-end -->
 *
 <!-- options-start -->
 * Valid options are: <p/>
 * 
 * <pre> -h
 *  Prints this help.</pre>
 * 
 * <pre> -o &lt;file&gt;
 *  The name of the output file, otherwise the generated data is
 *  printed to stdout.</pre>
 * 
 * <pre> -r &lt;name&gt;
 *  The name of the relation.</pre>
 * 
 * <pre> -d
 *  Whether to print debug informations.</pre>
 * 
 * <pre> -S
 *  The seed for random function (default 1)</pre>
 * 
 * <pre> -n &lt;num&gt;
 *  The number of examples to generate (default 100)</pre>
 * 
 * <pre> -F &lt;num&gt;
 *  The function to use for generating the data. (default 1)</pre>
 * 
 * <pre> -B
 *  Whether to balance the class.</pre>
 * 
 * <pre> -P &lt;num&gt;
 *  The perturbation factor. (default 0.05)</pre>
 * 
 <!-- options-end -->
 *
 * @author Richard Kirkby (rkirkby at cs dot waikato dot ac dot nz)
 * @author FracPete (fracpete at waikato dot ac dot nz)
 * @version $Revision: 1.5 $
 */

public class Agrawal
  extends ClassificationGenerator
  implements TechnicalInformationHandler {
  
  /** for serialization */
  static final long serialVersionUID = 2254651939636143025L;
  
  /**
   * the interface for the class functions
   */
  protected interface ClassFunction {
    /**
     * returns a class value based on the given inputs
     * @param salary the salary
     * @param commission the commission
     * @param age the age
     * @param elevel the education level
     * @param car 
     * @param zipcode the zip code
     * @param hvalue
     * @param hyears
     * @param loan
     */
    public long determineClass(double salary, double commission, int age,
        int elevel, int car, int zipcode, double hvalue, int hyears,
        double loan);
  }

  /** 
   * built in functions are based on the paper (page 924),
   * which turn out to be functions pred20 thru pred29 in the public c code
   */
  protected static ClassFunction[] builtInFunctions = {
    // function 1
    new ClassFunction() {
      public long determineClass(double salary, double commission,
          int age, int elevel, int car, int zipcode,
          double hvalue, int hyears, double loan) {
        if (age < 40 || 60 <= age)
          return 0;
        else
          return 1;
      }
    },
    // function 2
    new ClassFunction() {
      public long 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 0;
          else
            return 1;
        else if (age < 60) // && age >= 40
          if (75000 <= salary && salary <= 125000)
            return 0;
          else
            return 1;
        else // age >= 60
          if (25000 <= salary && salary <= 75000)
            return 0;
          else
            return 1;
      }
    },
    // function 3
    new ClassFunction() {
      public long 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 0;
          else
            return 1;
        else if (age < 60) // && age >= 40
          if (elevel == 1 || elevel == 2 || elevel == 3)
            return 0;
          else
            return 1;
        else // age >= 60
          if (elevel == 2 || elevel == 3 || elevel == 4)
            return 0;
          else
            return 1;
      }
    },
    // function 4
    new ClassFunction() {
      public long 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)
            if (25000 <= salary && salary <= 75000)
              return 0;
            else
              return 1;
          else if (50000 <= salary && salary <= 100000)
            return 0;
          else
            return 1;
        else if (age < 60) // && age >= 40
          if (elevel == 1 || elevel == 2 || elevel == 3)
            if (50000 <= salary && salary <= 100000)
              return 0;
            else
              return 1;
          else if (75000 <= salary && salary <= 125000)
            return 0;
          else
            return 1;
        else // age >= 60
          if (elevel == 2 || elevel == 3 || elevel == 4)
            if (50000 <= salary && salary <= 100000)
              return 0;
            else
              return 1;
          else if (25000 <= salary && salary <= 75000)
            return 0;
          else
            return 1;
      }
    },
    // function 5
    new ClassFunction() {
      public long 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)
            if (100000 <= loan && loan <= 300000)
              return 0;
            else
              return 1;
          else if (200000 <= loan && loan <= 400000)
            return 0;
          else
            return 1;
        else if (age < 60) // && age >= 40
          if (75000 <= salary && salary <= 125000)
            if (200000 <= loan && loan <= 400000)
              return 0;
            else
              return 1;
          else if (300000 <= loan && loan <= 500000)
            return 0;
          else
            return 1;
        else // age >= 60
          if (25000 <= salary && salary <= 75000)
            if (300000 <= loan && loan <= 500000)
              return 0;
            else
              return 1;
          else if (100000 <= loan && loan <= 300000)
            return 0;
          else
            return 1;
      }
    },
    // function 6
    new ClassFunction() {
      public long 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)
          if (50000 <= totalSalary && totalSalary <= 100000)
            return 0;
          else
            return 1;
        else if (age < 60) // && age >= 40
          if (75000 <= totalSalary && totalSalary <= 125000)
            return 0;
          else
            return 1;
        else // age >= 60
          if (25000 <= totalSalary && totalSalary <= 75000)
            return 0;
          else
            return 1;
      }
    },
    // function 7
    new ClassFunction() {
      public long 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 long 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 * (double) elevel - 20000.0);
        return disposable > 0 ? 0 : 1;
      }
    },
    // function 9
    new ClassFunction() {
      public long 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 * (double) elevel - loan / 5.0 - 10000.0);
        return disposable > 0 ? 0 : 1;
      }
    },
    // function 10
    new ClassFunction() {
      public long 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 * ((double) hyears - 20.0) / 10.0;
        double disposable = (2.0 * (salary + commission) / 3.0
            - 5000.0 * (double) elevel + equity / 5.0 - 10000.0);
        return disposable > 0 ? 0 : 1;
      }
    } 
  };

  /** function 1 */
  public final static int FUNCTION_1 = 1;
  /** function 2 */
  public final static int FUNCTION_2 = 2;
  /** function 3 */
  public final static int FUNCTION_3 = 3;
  /** function 4 */
  public final static int FUNCTION_4 = 4;
  /** function 5 */
  public final static int FUNCTION_5 = 5;
  /** function 6 */
  public final static int FUNCTION_6 = 6;
  /** function 7 */
  public final static int FUNCTION_7 = 7;
  /** function 8 */
  public final static int FUNCTION_8 = 8;
  /** function 9 */
  public final static int FUNCTION_9 = 9;
  /** function 10 */
  public final static int FUNCTION_10 = 10;
  /** the funtion tags */
  public static final Tag[] FUNCTION_TAGS = {
    new Tag(FUNCTION_1,  "Function 1"),
    new Tag(FUNCTION_2,  "Function 2"),
    new Tag(FUNCTION_3,  "Function 3"),
    new Tag(FUNCTION_4,  "Function 4"),
    new Tag(FUNCTION_5,  "Function 5"),
    new Tag(FUNCTION_6,  "Function 6"),
    new Tag(FUNCTION_7,  "Function 7"),
    new Tag(FUNCTION_8,  "Function 8"),
    new Tag(FUNCTION_9,  "Function 9"),
    new Tag(FUNCTION_10, "Function 10"),
  };
  
  /** the function to use for generating the data */
  protected int m_Function;

  /** whether to balance the class */
  protected boolean m_BalanceClass;

  /** the perturabation fraction */
  protected double m_PerturbationFraction;
  
  /** used for balancing the class */
  protected boolean m_nextClassShouldBeZero;

  /** the last class label that was generated */
  protected double m_lastLabel;
  
  /**
   * initializes the generator with default values
   */
  public Agrawal() {
    super();

    setFunction(defaultFunction());
    setBalanceClass(defaultBalanceClass());
    setPerturbationFraction(defaultPerturbationFraction());
  }

  /**
   * Returns a string describing this data generator.
   *
   * @return a description of the data generator suitable for
   * displaying in the explorer/experimenter gui
   */
  public String globalInfo() {
    return 
         "Generates a people database and is based on the paper by Agrawal "
       + "et al.:\n"
       + getTechnicalInformation().toString();
  }

  /**
   * Returns an instance of a TechnicalInformation object, containing 
   * detailed information about the technical background of this class,
   * e.g., paper reference or book this class is based on.
   * 
   * @return the technical information about this class
   */
  public TechnicalInformation getTechnicalInformation() {
    TechnicalInformation 	result;
    
    result = new TechnicalInformation(Type.ARTICLE);
    result.setValue(Field.AUTHOR, "R. Agrawal and T. Imielinski and A. Swami");
    result.setValue(Field.YEAR, "1993");
    result.setValue(Field.TITLE, "Database Mining: A Performance Perspective");
    result.setValue(Field.JOURNAL, "IEEE Transactions on Knowledge and Data Engineering");
    result.setValue(Field.VOLUME, "5");
    result.setValue(Field.NUMBER, "6");
    result.setValue(Field.PAGES, "914-925");
    result.setValue(Field.NOTE, "Special issue on Learning and Discovery in Knowledge-Based Databases");
    result.setValue(Field.URL, "http://www.almaden.ibm.com/software/quest/Publications/ByDate.html");
    result.setValue(Field.PDF, "http://www.almaden.ibm.com/software/quest/Publications/papers/tkde93.pdf");
    
    return result;
  }

 /**
   * Returns an enumeration describing the available options.
   *
   * @return an enumeration of all the available options
   */
  public Enumeration listOptions() {
    Vector result = enumToVector(super.listOptions());

    result.add(new Option(
              "\tThe function to use for generating the data. (default " 
              + defaultFunction().getSelectedTag().getID() + ")",
              "F", 1, "-F <num>"));

    result.add(new Option(
              "\tWhether to balance the class.",
              "B", 0, "-B"));

    result.add(new Option(
              "\tThe perturbation factor. (default " 
              + defaultPerturbationFraction() + ")",
              "P", 1, "-P <num>"));

    return result.elements();
  }

  /**
   * Parses a list of options for this object. <p/>
   *
   <!-- options-start -->
   * Valid options are: <p/>
   *