ILA: an inductive learning algorithm for rule extraction

In this paper we present a novel inductive learning algorithm called the Inductive Learning Algorithm (ILA) for extracting production rules from a set of examples. We also describe application of the ILA to a range of data sets with different numbers of attributes and classes. The results obtained show that the ILA is more general and robust than most other algorithms for inductive learning. Most of the time, ILA appears to be comparable to other well-known algorithms, such as AQ and ID3, if not better.