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Simple learning schemes for educational purposes (Prism, Id3, IB1 and NaiveBayesSimple).
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/*
* 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 3 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, see
*
* 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 ([email protected])
* @version $Revision: 8109 $
*/
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: 8109 $");
}
}
/**
* Class for storing a list of attribute-value tests
*/
private class Test
implements Serializable, RevisionHandler {
/** for serialization */
static final long serialVersionUID = -8925333011350280799L;
/** Attribute to test */
private int m_attr = -1;
/** The attribute's value */
private int m_val;
/** The next test in the rule */
private Test m_next = null;
/**
* Returns whether a given instance satisfies this test.
*
* @param inst the instance to be tested
* @return true if the instance satisfies the test
*/
private boolean satisfies(Instance inst) {
if ((int) inst.value(m_attr) == m_val) {
if (m_next == null) {
return true;
} else {
return m_next.satisfies(inst);
}
}
return false;
}
/**
* Returns the revision string.
*
* @return the revision
*/
public String getRevision() {
return RevisionUtils.extract("$Revision: 8109 $");
}
}
/** 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: 8109 $");
}
/**
* Main method for testing this class
*
* @param args the commandline parameters
*/
public static void main(String[] args) {
runClassifier(new Prism(), args);
}
}