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- # -*- coding: utf-8 -*-
- import unittest
- from nltk.classify.naivebayes import NaiveBayesClassifier
- class NaiveBayesClassifierTest(unittest.TestCase):
- 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')
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