A genetic algorithm for generalized rule induction

Data mining consists of the efficient discovery of knowledge from databases. This paper presents a new genetic algorithm designed for discovering a few interesting, high-level prediction rules from databases, rather than discovering classification knowledge (often a large rule set) as usual in the literature. Three important data mining issues addressed by our algorithm are the interestingness of the discovered knowledge, the computational efficiency of the algorithm, and the trade-off between representation expressiveness and efficiency.