001 package aima.learning.learners;
002
003 import java.util.ArrayList;
004 import java.util.List;
005
006 import aima.learning.framework.DataSet;
007 import aima.learning.framework.Example;
008 import aima.learning.framework.Learner;
009 import aima.learning.knowledge.CurrentBestLearning;
010 import aima.learning.knowledge.FOLDataSetDomain;
011 import aima.learning.knowledge.FOLExample;
012 import aima.learning.knowledge.Hypothesis;
013 import aima.logic.fol.inference.FOLOTTERLikeTheoremProver;
014 import aima.logic.fol.inference.InferenceResult;
015 import aima.logic.fol.kb.FOLKnowledgeBase;
016
017 /**
018 * @author Ciaran O'Reilly
019 *
020 */
021 public class CurrentBestLearner implements Learner {
022 private String trueGoalValue = null;
023 private FOLDataSetDomain folDSDomain = null;
024 private FOLKnowledgeBase kb = null;
025 private Hypothesis currentBestHypothesis = null;
026
027 //
028 // PUBLIC METHODS
029 //
030 public CurrentBestLearner(String trueGoalValue) {
031 this.trueGoalValue = trueGoalValue;
032 }
033
034 //
035 // START-Learner
036 public void train(DataSet ds) {
037 folDSDomain = new FOLDataSetDomain(ds.specification, trueGoalValue);
038 List<FOLExample> folExamples = new ArrayList<FOLExample>();
039 int egNo = 1;
040 for (Example e : ds.examples) {
041 folExamples.add(new FOLExample(folDSDomain, e, egNo));
042 egNo++;
043 }
044
045 // Setup a KB to be used for learning
046 kb = new FOLKnowledgeBase(folDSDomain, new FOLOTTERLikeTheoremProver(
047 1000, false));
048
049 CurrentBestLearning cbl = new CurrentBestLearning(folDSDomain, kb);
050
051 currentBestHypothesis = cbl.currentBestLearning(folExamples);
052 }
053
054 public String predict(Example e) {
055 String prediction = "~" + e.targetValue();
056 if (null != currentBestHypothesis) {
057 FOLExample etp = new FOLExample(folDSDomain, e, 0);
058 kb.clear();
059 kb.tell(etp.getDescription());
060 kb.tell(currentBestHypothesis.getHypothesis());
061 InferenceResult ir = kb.ask(etp.getClassification());
062 if (ir.isTrue()) {
063 if (trueGoalValue.equals(e.targetValue())) {
064 prediction = e.targetValue();
065 }
066 } else if (ir.isPossiblyFalse() || ir.isUnknownDueToTimeout()) {
067 if (!trueGoalValue.equals(e.targetValue())) {
068 prediction = e.targetValue();
069 }
070 }
071 }
072
073 return prediction;
074 }
075
076 public int[] test(DataSet ds) {
077 int[] results = new int[] { 0, 0 };
078
079 for (Example e : ds.examples) {
080 if (e.targetValue().equals(predict(e))) {
081 results[0] = results[0] + 1;
082 } else {
083 results[1] = results[1] + 1;
084 }
085 }
086 return results;
087 }
088 // END-Learner
089 //
090 }