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Python

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