001 /*
002 * Created on Jul 25, 2005
003 *
004 */
005 package aima.test.learningtest;
006
007 import java.util.ArrayList;
008
009 import junit.framework.TestCase;
010 import aima.learning.framework.DataSet;
011 import aima.learning.framework.DataSetFactory;
012 import aima.learning.inductive.DLTest;
013 import aima.learning.inductive.DLTestFactory;
014 import aima.learning.learners.CurrentBestLearner;
015 import aima.learning.learners.DecisionListLearner;
016 import aima.learning.learners.DecisionTreeLearner;
017 import aima.learning.learners.MajorityLearner;
018
019 /**
020 * @author Ravi Mohan
021 *
022 */
023
024 public class LearnerTests extends TestCase {
025 public void testMajorityLearner() throws Exception {
026 MajorityLearner learner = new MajorityLearner();
027 DataSet ds = DataSetFactory.getRestaurantDataSet();
028 learner.train(ds);
029 int[] result = learner.test(ds);
030 assertEquals(6, result[0]);
031 assertEquals(6, result[1]);
032 }
033
034 public void testDefaultUsedWhenTrainingDataSetHasNoExamples()
035 throws Exception {
036 // tests RecursionBaseCase#1
037 DataSet ds = DataSetFactory.getRestaurantDataSet();
038 DecisionTreeLearner learner = new DecisionTreeLearner();
039
040 DataSet ds2 = ds.emptyDataSet();
041 assertEquals(0, ds2.size());
042
043 learner.train(ds2);
044 assertEquals("Unable To Classify", learner.predict(ds.getExample(0)));
045
046 }
047
048 public void testClassificationReturnedWhenAllExamplesHaveTheSameClassification()
049 throws Exception {
050 // tests RecursionBaseCase#2
051 DataSet ds = DataSetFactory.getRestaurantDataSet();
052 DecisionTreeLearner learner = new DecisionTreeLearner();
053
054 DataSet ds2 = ds.emptyDataSet();
055
056 // all 3 examples have the same classification (willWait = yes)
057 ds2.add(ds.getExample(0));
058 ds2.add(ds.getExample(2));
059 ds2.add(ds.getExample(3));
060
061 learner.train(ds2);
062 assertEquals("Yes", learner.predict(ds.getExample(0)));
063
064 }
065
066 public void testMajorityReturnedWhenAttributesToExamineIsEmpty()
067 throws Exception {
068 // tests RecursionBaseCase#2
069 DataSet ds = DataSetFactory.getRestaurantDataSet();
070 DecisionTreeLearner learner = new DecisionTreeLearner();
071
072 DataSet ds2 = ds.emptyDataSet();
073
074 // 3 examples have classification = "yes" and one ,"no"
075 ds2.add(ds.getExample(0));
076 ds2.add(ds.getExample(1));// "no"
077 ds2.add(ds.getExample(2));
078 ds2.add(ds.getExample(3));
079 ds2.setSpecification(new MockDataSetSpecification("will_wait"));
080
081 learner.train(ds2);
082 assertEquals("Yes", learner.predict(ds.getExample(1)));
083
084 }
085
086 public void testInducedTreeClassifiesDataSetCorrectly() throws Exception {
087 DataSet ds = DataSetFactory.getRestaurantDataSet();
088 DecisionTreeLearner learner = new DecisionTreeLearner();
089 learner.train(ds);
090 int[] result = learner.test(ds);
091 assertEquals(12, result[0]);
092 assertEquals(0, result[1]);
093 }
094
095 public void testDecisionListLearnerReturnsNegativeDLWhenDataSetEmpty()
096 throws Exception {
097 // tests first base case of DL Learner
098 DecisionListLearner learner = new DecisionListLearner("Yes", "No",
099 new MockDLTestFactory(null));
100 DataSet ds = DataSetFactory.getRestaurantDataSet();
101 DataSet empty = ds.emptyDataSet();
102 learner.train(empty);
103 assertEquals("No", learner.predict(ds.getExample(0)));
104 assertEquals("No", learner.predict(ds.getExample(1)));
105 assertEquals("No", learner.predict(ds.getExample(2)));
106 }
107
108 public void testDecisionListLearnerReturnsFailureWhenTestsEmpty()
109 throws Exception {
110 // tests second base case of DL Learner
111 DecisionListLearner learner = new DecisionListLearner("Yes", "No",
112 new MockDLTestFactory(new ArrayList<DLTest>()));
113 DataSet ds = DataSetFactory.getRestaurantDataSet();
114 learner.train(ds);
115 assertEquals(DecisionListLearner.FAILURE, learner.predict(ds
116 .getExample(0)));
117 }
118
119 public void testDecisionListTestRunOnRestaurantDataSet() throws Exception {
120 DataSet ds = DataSetFactory.getRestaurantDataSet();
121 DecisionListLearner learner = new DecisionListLearner("Yes", "No",
122 new DLTestFactory());
123 learner.train(ds);
124 // System.out.println(learner.getDecisionList());
125 int[] result = learner.test(ds);
126 assertEquals(12, result[0]);
127 assertEquals(0, result[1]);
128 }
129
130 public void testCurrentBestLearnerOnRestaurantDataSet() throws Exception {
131 DataSet ds = DataSetFactory.getRestaurantDataSet();
132 CurrentBestLearner learner = new CurrentBestLearner("Yes");
133 learner.train(ds);
134
135 int[] result = learner.test(ds);
136 assertEquals(12, result[0]);
137 assertEquals(0, result[1]);
138 }
139 }