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)