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