AIMA.Core.Learning.Learners.DecisionTreeLearner.train C# (CSharp) Метод

        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)));
        }