Source code for nltk.test.unit.test_naivebayes

import unittest

from nltk.classify.naivebayes import NaiveBayesClassifier


[docs]class NaiveBayesClassifierTest(unittest.TestCase):
[docs] def test_simple(self): training_features = [ ({"nice": True, "good": True}, "positive"), ({"bad": True, "mean": True}, "negative"), ] classifier = NaiveBayesClassifier.train(training_features) result = classifier.prob_classify({"nice": True}) self.assertTrue(result.prob("positive") > result.prob("negative")) self.assertEqual(result.max(), "positive") result = classifier.prob_classify({"bad": True}) self.assertTrue(result.prob("positive") < result.prob("negative")) self.assertEqual(result.max(), "negative")