def main():
# load training files into Classifier
path_to_res = os.path.join(sys.path[0], "resources\\")
neg_classif = Classifier(path_to_res + "training_negative.txt")
neu_classif = Classifier(path_to_res + "training_neutral.txt")
pos_classif = Classifier(path_to_res + "training_positive.txt")
total_entries = neu_classif.get_entries() + neg_classif.get_entries() + pos_classif.get_entries()
# load test files
test_parser = Parser(path_to_res + "test_set.txt")
counter = 1
while(True):
word_list = test_parser.giveWordList()
if len(word_list) == 0:
break
neg_p = neg_classif.classification_probability(word_list, total_entries)
neu_p = neu_classif.classification_probability(word_list, total_entries)
pos_p = pos_classif.classification_probability(word_list, total_entries)
print("Test " + str(counter) + ":\n")
print("\tNegative: " + str(math.fabs(neg_p)) + "%\n")
print("\tNeutral: " + str(math.fabs(neu_p)) + "%\n")
print("\tPositve: " + str(math.fabs(pos_p)) + "%\n")
counter += 1
