peacock-data-public-datasets-idc-cronscript
/
venv
/lib
/python3.10
/site-packages
/nltk
/test
/unit
/test_naivebayes.py
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") | |