### Question:
UniversalClassifier extends AbstractLearner<UniversalClassifierModel> implements Classifier<UniversalClassifierModel> { @Override public UniversalClassifierModel train(Dataset dataset) { NaiveBayesModel nominalModel = null; KnnModel numericModel = null; DictionaryModel textModel = null; if (settings.contains(ClassifierSetting.TEXT)) { LOGGER.debug("training text classifier"); textModel = textClassifier.train(dataset); } if (settings.contains(ClassifierSetting.KNN)) { LOGGER.debug("training knn classifier"); numericModel = new KnnLearner(new NoNormalizer()).train(dataset); } if (settings.contains(ClassifierSetting.BAYES)) { LOGGER.debug("training bayes classifier"); nominalModel = new NaiveBayesLearner().train(dataset); } return new UniversalClassifierModel(nominalModel, numericModel, textModel); } UniversalClassifier();  UniversalClassifier(FeatureSetting featureSetting, ClassifierSetting... settings); @Override UniversalClassifierModel train(Dataset dataset); @Override CategoryEntries classify(FeatureVector featureVector, UniversalClassifierModel model);  }### Answer:
@Test @Ignore public void test() throws FileNotFoundException { File datasetFile = getResourceFile("/classifier/saheart.csv"); List<Instance> instances = new CsvDatasetReader(datasetFile, true, ",").readAll(); List<Instance> trainingSet = new ArrayList<Instance>(instances.subList(0, (int)(instances.size() * 0.6))); instances.removeAll(trainingSet); UniversalClassifier objectOfClassUnderTest = new UniversalClassifier(FeatureSettingBuilder.words().create(),BAYES, KNN); UniversalClassifierModel model = objectOfClassUnderTest.train(trainingSet); assertEquals(2, model.getCategories().size()); assertTrue(model.getCategories().contains("0")); assertTrue(model.getCategories().contains("1")); ConfusionMatrix matrix = ClassifierEvaluation.evaluate(objectOfClassUnderTest, instances, model); System.out.println(matrix); assertTrue(matrix.getPrecision("1") > 0.57); assertTrue(matrix.getRecall("1") > 0.56); assertTrue(matrix.getF(1.0, "1") > 0.56); }