AN ALGORITHM FOR INCREMENTAL INDUCTIVE LEARNING

This paper describes RULES-4, a new algorithm for incremental inductiv e learning from the 'RULES' family of automatic rule extraction system s. This algorithm is the first incremental learning system in the fami ly. It has a number of advantages over well-known non-incremental sche mes. It allows the stored knowledge to be updated and refined rapidly when new examples are available. The induction of rules for a process planning expert system is used to illustrate the operation of RULES-4 and a bench-mark pattern classification problem employed to test the a lgorithm. The results obtained have shown that the accuracy of the ext racted rule sets is commensurate with the accuracy of the rule set obt ained using a non-incremental algorithm.