/* * 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. */ /* * Prism.java * Copyright (C) 1999 University of Waikato, Hamilton, New Zealand * */ package weka.classifiers.rules; import weka.classifiers.Classifier; import weka.classifiers.AbstractClassifier; import weka.core.Attribute; import weka.core.Capabilities; import weka.core.Instance; import weka.core.Instances; import weka.core.RevisionHandler; import weka.core.RevisionUtils; import weka.core.TechnicalInformation; import weka.core.TechnicalInformationHandler; import weka.core.Capabilities.Capability; import weka.core.TechnicalInformation.Field; import weka.core.TechnicalInformation.Type; import weka.core.Utils; import java.io.Serializable; import java.util.Enumeration; /** * Class for building and using a PRISM rule set for classification. Can only deal with nominal attributes. Can't deal with missing values. Doesn't do any pruning.
*
* For more information, see
*
* J. Cendrowska (1987). PRISM: An algorithm for inducing modular rules. International Journal of Man-Machine Studies. 27(4):349-370. *

* * BibTeX: *

 * @article{Cendrowska1987,
 *    author = {J. Cendrowska},
 *    journal = {International Journal of Man-Machine Studies},
 *    number = {4},
 *    pages = {349-370},
 *    title = {PRISM: An algorithm for inducing modular rules},
 *    volume = {27},
 *    year = {1987}
 * }
 * 
*

* * Valid options are:

* *

 -D
 *  If set, classifier is run in debug mode and
 *  may output additional info to the console
* * * @author Ian H. Witten (ihw@cs.waikato.ac.nz) * @version $Revision: 5987 $ */ public class Prism extends AbstractClassifier implements TechnicalInformationHandler { /** for serialization */ static final long serialVersionUID = 1310258880025902106L; /** * Returns a string describing classifier * @return a description suitable for * displaying in the explorer/experimenter gui */ public String globalInfo() { return "Class for building and using a PRISM rule set for classification. " + "Can only deal with nominal attributes. Can't deal with missing values. " + "Doesn't do any pruning.\n\n" + "For more information, see \n\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, "J. Cendrowska"); result.setValue(Field.YEAR, "1987"); result.setValue(Field.TITLE, "PRISM: An algorithm for inducing modular rules"); result.setValue(Field.JOURNAL, "International Journal of Man-Machine Studies"); result.setValue(Field.VOLUME, "27"); result.setValue(Field.NUMBER, "4"); result.setValue(Field.PAGES, "349-370"); return result; } /** * Class for storing a PRISM ruleset, i.e. a list of rules */ private class PrismRule implements Serializable, RevisionHandler { /** for serialization */ static final long serialVersionUID = 4248784350656508583L; /** The classification */ private int m_classification; /** The instance */ private Instances m_instances; /** First test of this rule */ private Test m_test; /** Number of errors made by this rule (will end up 0) */ private int m_errors; /** The next rule in the list */ private PrismRule m_next; /** * Constructor that takes instances and the classification. * * @param data the instances * @param cl the class * @exception Exception if something goes wrong */ public PrismRule(Instances data, int cl) throws Exception { m_instances = data; m_classification = cl; m_test = null; m_next = null; m_errors = 0; Enumeration enu = data.enumerateInstances(); while (enu.hasMoreElements()) { if ((int) ((Instance) enu.nextElement()).classValue() != cl) { m_errors++; } } m_instances = new Instances(m_instances, 0); } /** * Returns the result assigned by this rule to a given instance. * * @param inst the instance to be classified * @return the classification */ public int resultRule(Instance inst) { if (m_test == null || m_test.satisfies(inst)) { return m_classification; } else { return -1; } } /** * Returns the result assigned by these rules to a given instance. * * @param inst the instance to be classified * @return the classification */ public int resultRules(Instance inst) { if (resultRule(inst) != -1) { return m_classification; } else if (m_next != null) { return m_next.resultRules(inst); } else { return -1; } } /** * Returns the set of instances that are covered by this rule. * * @param data the instances to be checked * @return the instances covered */ public Instances coveredBy(Instances data) { Instances r = new Instances(data, data.numInstances()); Enumeration enu = data.enumerateInstances(); while (enu.hasMoreElements()) { Instance i = (Instance) enu.nextElement(); if (resultRule(i) != -1) { r.add(i); } } r.compactify(); return r; } /** * Returns the set of instances that are not covered by this rule. * * @param data the instances to be checked * @return the instances not covered */ public Instances notCoveredBy(Instances data) { Instances r = new Instances(data, data.numInstances()); Enumeration enu = data.enumerateInstances(); while (enu.hasMoreElements()) { Instance i = (Instance) enu.nextElement(); if (resultRule(i) == -1) { r.add(i); } } r.compactify(); return r; } /** * Prints the set of rules. * * @return a description of the rules as a string */ public String toString() { try { StringBuffer text = new StringBuffer(); if (m_test != null) { text.append("If "); for (Test t = m_test; t != null; t = t.m_next) { if (t.m_attr == -1) { text.append("?"); } else { text.append(m_instances.attribute(t.m_attr).name() + " = " + m_instances.attribute(t.m_attr).value(t.m_val)); } if (t.m_next != null) { text.append("\n and "); } } text.append(" then "); } text.append(m_instances.classAttribute().value(m_classification) + "\n"); if (m_next != null) { text.append(m_next.toString()); } return text.toString(); } catch (Exception e) { return "Can't print Prism classifier!"; } } /** * Returns the revision string. * * @return the revision */ public String getRevision() { return RevisionUtils.extract("$Revision: 5987 $"); } } /** * Class for storing a list of attribute-value tests */ private class Test implements Serializable, RevisionHandler { /** for serialization */ static final long serialVersionUID = -8925333011350280799L; /** Attribute to test */ private int m_attr = -1; /** The attribute's value */ private int m_val; /** The next test in the rule */ private Test m_next = null; /** * Returns whether a given instance satisfies this test. * * @param inst the instance to be tested * @return true if the instance satisfies the test */ private boolean satisfies(Instance inst) { if ((int) inst.value(m_attr) == m_val) { if (m_next == null) { return true; } else { return m_next.satisfies(inst); } } return false; } /** * Returns the revision string. * * @return the revision */ public String getRevision() { return RevisionUtils.extract("$Revision: 5987 $"); } } /** The first rule in the list of rules */ private PrismRule m_rules; /** * Classifies a given instance. * * @param inst the instance to be classified * @return the classification */ public double classifyInstance(Instance inst) { int result = m_rules.resultRules(inst); if (result == -1) { return Utils.missingValue(); } else { return (double)result; } } /** * Returns default capabilities of the classifier. * * @return the capabilities of this classifier */ public Capabilities getCapabilities() { Capabilities result = super.getCapabilities(); result.disableAll(); // attributes result.enable(Capability.NOMINAL_ATTRIBUTES); // class result.enable(Capability.NOMINAL_CLASS); result.enable(Capability.MISSING_CLASS_VALUES); return result; } /** * Generates the classifier. * * @param data the data to be used * @exception Exception if the classifier can't built successfully */ public void buildClassifier(Instances data) throws Exception { int cl; // possible value of theClass Instances E, ruleE; PrismRule rule = null; Test test = null, oldTest = null; int bestCorrect, bestCovers, attUsed; Enumeration enumAtt; // can classifier handle the data? getCapabilities().testWithFail(data); // remove instances with missing class data = new Instances(data); data.deleteWithMissingClass(); for (cl = 0; cl < data.numClasses(); cl++) { // for each class cl E = data; // initialize E to the instance set while (contains(E, cl)) { // while E contains examples in class cl rule = addRule(rule, new PrismRule(E, cl)); // make a new rule ruleE = E; // examples covered by this rule while (rule.m_errors != 0) { // until the rule is perfect test = new Test(); // make a new test bestCorrect = bestCovers = attUsed = 0; // for every attribute not mentioned in the rule enumAtt = ruleE.enumerateAttributes(); while (enumAtt.hasMoreElements()) { Attribute attr = (Attribute) enumAtt.nextElement(); if (isMentionedIn(attr, rule.m_test)) { attUsed++; continue; } int M = attr.numValues(); int[] covers = new int [M]; int[] correct = new int [M]; for (int j = 0; j < M; j++) { covers[j] = correct[j] = 0; } // ... calculate the counts for this class Enumeration enu = ruleE.enumerateInstances(); while (enu.hasMoreElements()) { Instance i = (Instance) enu.nextElement(); covers[(int) i.value(attr)]++; if ((int) i.classValue() == cl) { correct[(int) i.value(attr)]++; } } // ... for each value of this attribute, see if this test is better for (int val = 0; val < M; val ++) { int diff = correct[val] * bestCovers - bestCorrect * covers[val]; // this is a ratio test, correct/covers vs best correct/covers if (test.m_attr == -1 || diff > 0 || (diff == 0 && correct[val] > bestCorrect)) { // update the rule to use this test bestCorrect = correct[val]; bestCovers = covers[val]; test.m_attr = attr.index(); test.m_val = val; rule.m_errors = bestCovers - bestCorrect; } } } if (test.m_attr == -1) { // Couldn't find any sensible test break; } oldTest = addTest(rule, oldTest, test); ruleE = rule.coveredBy(ruleE); if (attUsed == (data.numAttributes() - 1)) { // Used all attributes. break; } } E = rule.notCoveredBy(E); } } } /** * Add a rule to the ruleset. * * @param lastRule the last rule in the rule set * @param newRule the rule to be added * @return the new last rule in the rule set */ private PrismRule addRule(PrismRule lastRule, PrismRule newRule) { if (lastRule == null) { m_rules = newRule; } else { lastRule.m_next = newRule; } return newRule; } /** * Add a test to this rule. * * @param rule the rule to which test is to be added * @param lastTest the rule's last test * @param newTest the test to be added * @return the new last test of the rule */ private Test addTest(PrismRule rule, Test lastTest, Test newTest) { if (rule.m_test == null) { rule.m_test = newTest; } else { lastTest.m_next = newTest; } return newTest; } /** * Does E contain any examples in the class C? * * @param E the instances to be checked * @param C the class * @return true if there are any instances of class C * @throws Exception if something goes wrong */ private static boolean contains(Instances E, int C) throws Exception { Enumeration enu = E.enumerateInstances(); while (enu.hasMoreElements()) { if ((int) ((Instance) enu.nextElement()).classValue() == C) { return true; } } return false; } /** * Is this attribute mentioned in the rule? * * @param attr the attribute to be checked for * @param t test contained by rule * @return true if the attribute is mentioned in the rule */ private static boolean isMentionedIn(Attribute attr, Test t) { if (t == null) { return false; } if (t.m_attr == attr.index()) { return true; } return isMentionedIn(attr, t.m_next); } /** * Prints a description of the classifier. * * @return a description of the classifier as a string */ public String toString() { if (m_rules == null) { return "Prism: No model built yet."; } return "Prism rules\n----------\n" + m_rules.toString(); } /** * Returns the revision string. * * @return the revision */ public String getRevision() { return RevisionUtils.extract("$Revision: 5987 $"); } /** * Main method for testing this class * * @param args the commandline parameters */ public static void main(String[] args) { runClassifier(new Prism(), args); } }