public void TestClassify() { SimpleWordsDataSource wds = new SimpleWordsDataSource(); BayesianClassifier classifier = new BayesianClassifier(wds); string[] sentence = new string[] { "This", "is", "a", "sentence", "about", "java" }; Assert.AreEqual(IClassifierConstants.NEUTRAL_PROBABILITY, classifier.Classify(ICategorizedClassifierConstants.DEFAULT_CATEGORY, sentence), 0d); wds.SetWordProbability(new WordProbability("This", .5d)); wds.SetWordProbability(new WordProbability("is", .5d)); wds.SetWordProbability(new WordProbability("a", .5d)); wds.SetWordProbability(new WordProbability("sentence", .2d)); wds.SetWordProbability(new WordProbability("about", .5d)); wds.SetWordProbability(new WordProbability("java", .99d)); Assert.AreEqual(.96d, classifier.Classify(ICategorizedClassifierConstants.DEFAULT_CATEGORY, sentence), .009d); }
public void ClassifierTest() { var bc = new BayesianClassifier <int>(); bc.SetFeatureProbability(10, .50d); bc.SetFeatureProbability(20, .2d); bc.SetFeatureProbability(30, .50d); bc.SetFeatureProbability(69, .99d); var set = bc.Classify(new[] { 10, 20, 30, 69 }); Assert.NotNull(set); Assert.AreEqual(1, set.Count); var r = set.ElementAt(0); Assert.AreEqual(.96d, r.Probability, .009d); }
public void ClassifierTest() { var bc = new BayesianClassifier<int>(); bc.SetFeatureProbability(10, .50d); bc.SetFeatureProbability(20, .2d); bc.SetFeatureProbability(30, .50d); bc.SetFeatureProbability(69, .99d); var set = bc.Classify(new[] { 10, 20, 30, 69 }); Assert.NotNull(set); Assert.AreEqual(1, set.Count); var r = set.ElementAt(0); Assert.AreEqual(.96d, r.Probability, .009d); }