def classify_messages(self):
"""c
"""
messages = self.test_messages
classes = self.classes
for message in messages:
if self.agent_type == "spam":
to_copy = CLASSMAPSPAM
else:
to_copy = CLASSMAP8
MAP_values = deepcopy(to_copy)
ML_values = deepcopy(to_copy)
for key in MAP_values:
aClass = classes[key]
P_aClass = log(self.p_of_class(aClass))
MAP_values[key] = P_aClass
ML_values[key] = 0
word_dict = message.word_dict
for word in word_dict:
for key in classes:
pwgc = p_of_word_given_class(
word,
classes[key]
)
MAP_values[key] += log(pwgc)
ML_values[key] += log(pwgc)
message.classification =\
Classification(MAP_values, ML_values)
def odds(word, class_1, class_2):
"""c
"""
pwgc1 = p_of_word_given_class(word, class_1)
pwgc2 = p_of_word_given_class(word, class_2)
return log(ratio(pwgc1, pwgc2))