public void testDLTestReturnsMatchedAndUnmatchedExamplesCorrectly()
{
DataSet ds = DataSetFactory.getRestaurantDataSet();
DLTest test = new DLTest();
test.add("type", "Burger");
DataSet matched = test.matchedExamples(ds);
Assert.AreEqual(4, matched.size());
DataSet unmatched = test.unmatchedExamples(ds);
Assert.AreEqual(8, unmatched.size());
}
//
// PRIVATE METHODS
//
private DecisionList decisionListLearning(DataSet ds)
{
if (ds.size() == 0)
{
return(new DecisionList(positive, negative));
}
List <DLTest> possibleTests = testFactory
.createDLTestsWithAttributeCount(ds, 1);
DLTest test = getValidTest(possibleTests, ds);
if (test == null)
{
return(new DecisionList(null, FAILURE));
}
// at this point there is a test that classifies some subset of examples
// with the same target value
DataSet matched = test.matchedExamples(ds);
DecisionList list = new DecisionList(positive, negative);
list.add(test, matched.getExample(0).targetValue());
return(list.mergeWith(decisionListLearning(test.unmatchedExamples(ds))));
}
