An algorithm for incremental inductive learning

Abstract

This paper describes RULES-4, a new algorithm for incremental inductive learning from the ‘RULES’ family of automatic rule extraction systems. This algorithm is the first incremental learning system in the family. It has a number of advantages over well-known non-incremental schemes. 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 algorithm. The results obtained have shown that the accuracy of the extracted rule sets is commensurate with the accuracy of the rule set obtained using a non-incremental algorithm.