Efficient rule induction from noisy data

The single-pattern-based rule induction method is sensitive to the order of data. Naturally, it is not suitable for data with noise. This paper reports a new rule induction method of this kind that handles noise effectively. Experiments are conducted to show that rules generated are compact and accurate, and the method is efficient and handles noise effectively. Its computational complexity is also given for comparison with other methods and as a guide for future application of this method.