In this paper we describe the ILA-2 rule induction algorithm, which is the improved version of a novel inductive learning algorithm (ILA). We first outline the basic algorithm ILA, and then present how the algorithm is improved using a new evaluation metric that handles uncertainty in the data. By using a new soft computing metric, users can reflect their preferences through a penalty factor to control the performance of the algorithm. Inductive learning algorithm has also a faster pass criteria feature which reduces the processing time without sacrificing much from the accuracy that is not available in basic ILA.
ASJC Scopus subject areas
- Human-Computer Interaction
- Control and Systems Engineering