def test(self, directory):
corp = Corpus(directory)
result = {}
if self.trained:
for fname, body in corp.emails():
SpamSum = 0
HamSum = 0
examined = Email(fname, body)
for spam in self.spams:
SpamSum += Email.compare_emails(examined, spam)
for ham in self.hams:
HamSum += Email.compare_emails(examined, ham)
if SpamSum / len(self.spams) > HamSum / len(self.hams):
result[fname] = 'SPAM'
else:
result[fname] = 'OK'
write_classification_to_file(
directory + os.path.sep + '!prediction.txt', result)
else:
for fname, body in corp.emails():
counter = 0
for word in self.blacklist:
if word in body:
counter += 1
if counter > 3:
result[fname] = 'SPAM'
else:
result[fname] = 'OK'
write_classification_to_file(
directory + os.path.sep + '!prediction.txt', result)
