train() public méthode

public train ( DataSet ds ) : void
ds AIMA.Core.Learning.Framework.DataSet
Résultat void
DecisionListLearner Class Documentation
Exemple #1
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        public void testDecisionListTestRunOnRestaurantDataSet()
        {
            DataSet ds = DataSetFactory.getRestaurantDataSet();
            DecisionListLearner learner = new DecisionListLearner("Yes", "No",
                    new DLTestFactory());
            learner.train(ds);

            int[] result = learner.test(ds);
            Assert.AreEqual(12, result[0]);
            Assert.AreEqual(0, result[1]);
        }
Exemple #2
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 public void testDecisionListLearnerReturnsNegativeDLWhenDataSetEmpty()
 {
     // tests first base case of DL Learner
     DecisionListLearner learner = new DecisionListLearner("Yes", "No",
             new MockDLTestFactory(null));
     DataSet ds = DataSetFactory.getRestaurantDataSet();
     DataSet empty = ds.emptyDataSet();
     learner.train(empty);
     Assert.AreEqual("No", learner.predict(ds.getExample(0)));
     Assert.AreEqual("No", learner.predict(ds.getExample(1)));
     Assert.AreEqual("No", learner.predict(ds.getExample(2)));
 }
Exemple #3
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 public void testDecisionListLearnerReturnsFailureWhenTestsEmpty()
 {
     // tests second base case of DL Learner
     DecisionListLearner learner = new DecisionListLearner("Yes", "No",
             new MockDLTestFactory(new List<DLTest>()));
     DataSet ds = DataSetFactory.getRestaurantDataSet();
     learner.train(ds);
     Assert.AreEqual(DecisionListLearner.FAILURE, learner.predict(ds
             .getExample(0)));
 }