50 lines
1.3 KiB
Python
50 lines
1.3 KiB
Python
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"""
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Unit tests for nltk.classify. See also: nltk/test/classify.doctest
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"""
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import pytest
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from nltk import classify
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TRAIN = [
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(dict(a=1, b=1, c=1), "y"),
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(dict(a=1, b=1, c=1), "x"),
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(dict(a=1, b=1, c=0), "y"),
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(dict(a=0, b=1, c=1), "x"),
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(dict(a=0, b=1, c=1), "y"),
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(dict(a=0, b=0, c=1), "y"),
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(dict(a=0, b=1, c=0), "x"),
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(dict(a=0, b=0, c=0), "x"),
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(dict(a=0, b=1, c=1), "y"),
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]
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TEST = [
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(dict(a=1, b=0, c=1)), # unseen
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(dict(a=1, b=0, c=0)), # unseen
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(dict(a=0, b=1, c=1)), # seen 3 times, labels=y,y,x
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(dict(a=0, b=1, c=0)), # seen 1 time, label=x
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]
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RESULTS = [(0.16, 0.84), (0.46, 0.54), (0.41, 0.59), (0.76, 0.24)]
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def assert_classifier_correct(algorithm):
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try:
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classifier = classify.MaxentClassifier.train(
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TRAIN, algorithm, trace=0, max_iter=1000
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)
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except (LookupError, AttributeError) as e:
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pytest.skip(str(e))
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for (px, py), featureset in zip(RESULTS, TEST):
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pdist = classifier.prob_classify(featureset)
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assert abs(pdist.prob("x") - px) < 1e-2, (pdist.prob("x"), px)
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assert abs(pdist.prob("y") - py) < 1e-2, (pdist.prob("y"), py)
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def test_megam():
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assert_classifier_correct("MEGAM")
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def test_tadm():
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assert_classifier_correct("TADM")
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