def test_validate(self):
"""cross validates with an error of 35% or less"""
neg = self.split_file('data/rt-polaritydata/rt-polarity.neg')
pos = self.split_file('data/rt-polaritydata/rt-polarity.pos')
classifier = SentimentClassifier.build(
[neg['training'], pos['training']])
c = 2**7
classifier.c = c
classifier.reset_model()
n_er = self.validate(classifier, neg['validation'], 'negative')
p_er = self.validate(classifier, pos['validation'], 'positive')
total = Fraction(n_er.numerator + p_er.numerator,
n_er.denominator + p_er.denominator)
print(total)
self.assertLess(total, 0.35)
def test_validate(self):
"""cross validates with an error of 35% or less"""
neg = self.split_file('data/rt-polaritydata/rt-polarity.neg')
pos = self.split_file('data/rt-polaritydata/rt-polarity.pos')
classifier = SentimentClassifier.build([
neg['training'],
pos['training']
])
c = 2 ** 7
classifier.c = c
classifier.reset_model()
n_er = self.validate(classifier, neg['validation'], 'negative')
p_er = self.validate(classifier, pos['validation'], 'positive')
total = Fraction(n_er.numerator + p_er.numerator,
n_er.denominator + p_er.denominator)
print(total)
self.assertLess(total, 0.35)
def test_validate_itself(self):
"""yields a zero error when it uses itself"""
classifier = SentimentClassifier.build([
'data/rt-polaritydata/rt-polarity.neg',
'data/rt-polaritydata/rt-polarity.pos'
])
c = 2 ** 7
classifier.c = c
classifier.reset_model()
n_er = self.validate(classifier,
'data/rt-polaritydata/rt-polarity.neg',
'negative')
p_er = self.validate(classifier,
'data/rt-polaritydata/rt-polarity.pos',
'positive')
total = Fraction(n_er.numerator + p_er.numerator,
n_er.denominator + p_er.denominator)
print(total)
self.assertEqual(total, 0)
def test_validate_itself(self):
"""yields a zero error when it uses itself"""
classifier = SentimentClassifier.build([
'data/rt-polaritydata/rt-polarity.neg',
'data/rt-polaritydata/rt-polarity.pos'
])
c = 2**7
classifier.c = c
classifier.reset_model()
n_er = self.validate(classifier,
'data/rt-polaritydata/rt-polarity.neg',
'negative')
p_er = self.validate(classifier,
'data/rt-polaritydata/rt-polarity.pos',
'positive')
total = Fraction(n_er.numerator + p_er.numerator,
n_er.denominator + p_er.denominator)
print(total)
self.assertEqual(total, 0)