Abstract
This paper describes RULES3-EXT, a new algorithm for inductive learning. It has been developed to cope with some drawbacks of RULES-3 induction algorithm. The extra features of RULES3-EXT are (1) The number of required files to extract a knowledge base (a set of rules) is reduced to 2 from 3 (2) The repeated examples are eliminated, (3) The users are able to change the order of attributes and (4) The system is able to fire rule(s) partially if any of the extracted rules cannot fully be satisfied by an unseen example. The new algorithm has been tested on well known data sets and the efficiency found to be superior to that of RULES-3.