public virtual void train(DataSet ds)
{
List<String> attributes = ds.getNonTargetAttributes();
this.tree = decisionTreeLearning(ds, attributes,
new ConstantDecisonTree(defaultValue));
}
public void testDefaultUsedWhenTrainingDataSetHasNoExamples() { // tests RecursionBaseCase#1 DataSet ds = DataSetFactory.getRestaurantDataSet(); DecisionTreeLearner learner = new DecisionTreeLearner(); DataSet ds2 = ds.emptyDataSet(); Assert.AreEqual(0, ds2.size()); learner.train(ds2); Assert.AreEqual("Unable To Classify", learner.predict(ds .getExample(0))); }