Source code for nltk.test.unit.test_naivebayes

# -*- coding: utf-8 -*-
from __future__ import print_function, unicode_literals


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')