def parse(args):
id3 = DecisionTree(DecisionTree.Mode(args.mode))
train_data = load_file(f"data/train_c{args.clause}_d{args.sample}.csv")
valid_data = load_file(f"data/valid_c{args.clause}_d{args.sample}.csv")
test_data = load_file(f"data/test_c{args.clause}_d{args.sample}.csv")
id3.train(train_data)
if args.dbp:
print(id3.depth_based_prune(valid_data, [5, 10, 15, 20, 50, 100]))
if args.rep:
id3.reduced_error_prune(valid_data)
accuracy = id3.test(test_data)
print(accuracy)
