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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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