def docprob(bayes, item, cat):
"""Zadanie 604"""
features = bayes.get_features(item)
features_sum = 0
for feature in features:
features_sum = features_sum + featprob(bayes, feature, cat)
return catprob(bayes, cat) + features_sum
def docprob(bayes, item, cat):
"""Zadanie 604"""
features = bayes.get_features(item)
features_sum = 0
for feature in features:
features_sum = features_sum + featprob(bayes, feature, cat)
return catprob(bayes, cat) + features_sum
def test(self):
"""Test na sztucznych danych."""
def getfeatures(text):
"""Funkcja do testów."""
return list(set(text.split()))
bayes = NaiveBayes.NaiveBayes(getfeatures)
bayes.feature_count = {('terms,', 'C1'): 1, ('considers', 'C2'): 1,
('independently', 'C3'): 1, ('each', 'C1'): 1,
('that', 'C1'): 1, ('the', 'C3'): 1, ('on', 'C1'): 1,
('features', 'C1'): 1, ('and', 'C3'): 1, ('is', 'C2'): 1,
('feature.', 'C2'): 1, ('For', 'C2'): 1, ('fruit', 'C2'): 1,
('features,', 'C2'): 1, ('classifier', 'C2'): 1,
('(or', 'C2'): 2, ('these', 'C1'): 1, ('the', 'C2'): 2,
('particular', 'C2'): 1, ('may', 'C2'): 1,
('Bayes', 'C2'): 1, ('all', 'C2'): 1, ('feature', 'C2'): 1,
('apple', 'C3'): 1, ('naive', 'C2'): 1, ('depend', 'C1'): 1,
('other', 'C2'): 2, ('if', 'C3'): 1,
('contribute', 'C3'): 1, ('any', 'C2'): 1,
('these', 'C2'): 1, ('4"', 'C3'): 1,
('classifier', 'C1'): 1, ('other', 'C1'): 1,
('of', 'C1'): 1, ('assumes', 'C1'): 1,
('Bayes', 'C1'): 1, ('Even', 'C1'): 1,
('presence', 'C1'): 1, ('the', 'C1'): 2,
('a', 'C2'): 3, ('upon', 'C1'): 1,
('that', 'C3'): 1, ('example,', 'C2'): 1,
('properties', 'C3'): 1, ('this', 'C3'): 1,
('to', 'C2'): 1, ('In', 'C1'): 1,
('round,', 'C3'): 1, ('about', 'C3'): 1,
('absence)', 'C2'): 2, ('of', 'C2'): 3,
('diameter.', 'C3'): 1,
('existence', 'C1'): 1, ('be', 'C3'): 1,
('considered', 'C3'): 1, ('a', 'C1'): 1,
('it', 'C3'): 1, ('an', 'C3'): 1,
('or', 'C1'): 1, ('if', 'C1'): 1,
('presence', 'C2'): 1, ('is', 'C3'): 1,
('to', 'C3'): 2, ('unrelated', 'C2'): 1,
('red,', 'C3'): 1, ('probability', 'C3'): 1,
('naive', 'C1'): 1, ('class', 'C2'): 1,
('in', 'C3'): 1, ('simple', 'C1'): 1}
bayes.class_count = {'C1': 2, 'C2': 3, 'C3': 2}
feat_cats = [
('of', 'C2'), ('to', 'C3'), ('features', 'C1'),
('Bayes', 'C1'), ('of', 'C1'),
('to', 'C5'), ('features', 'C3'), ('Bayes', 'C2')]
probs = [0.0, 0.0, -0.6931,
-0.6931, -0.6931,
-1e+300, -7.6009, -1.0986]
for idx in range(len(feat_cats)):
self.assertAlmostEqual(
featprob(bayes, feat_cats[idx][0], feat_cats[idx][1]),
probs[idx], 4)