public void testInducedDecisionTreeClassifiesRestaurantDataSetCorrectly()
{
DecisionTreeLearner learner = new DecisionTreeLearner(
createInducedRestaurantDecisionTree(), "Unable to clasify");
int[] results = learner.test(DataSetFactory.getRestaurantDataSet());
Assert.AreEqual(12, results[0]);
Assert.AreEqual(0, results[1]);
}
public void testInducedTreeClassifiesDataSetCorrectly()
{
DataSet ds = DataSetFactory.getRestaurantDataSet();
DecisionTreeLearner learner = new DecisionTreeLearner();
learner.train(ds);
int[] result = learner.test(ds);
Assert.AreEqual(12, result[0]);
Assert.AreEqual(0, result[1]);
}
public void testStumpPredictionForDataSet()
{
DataSet ds = DataSetFactory.getRestaurantDataSet();
List <String> unmatchedValues = new List <String>();
unmatchedValues.Add(NO);
DecisionTree tree = DecisionTree.getStumpFor(ds, "hungry", YES, YES,
unmatchedValues, "Unable to Classify");
DecisionTreeLearner learner = new DecisionTreeLearner(tree,
"Unable to Classify");
int[] result = learner.test(ds);
Assert.AreEqual(5, result[0]);
Assert.AreEqual(7, result[1]);
}