Rule Discovery with a Parallel Genetic Algorithm
Dieferson L.A. Araujo, Heitor Silvério Lopes, Alex Alves Freitas · Kent Academic Repository (University of Kent) · 2000
An important issue in data mining is scalability with respect to the size of the dataset being mined. In the paper we address this issue by presenting a parallel GA for rule discovery. This algorithm exploits both data parallelism, by distributing the data being mined across all available processors, and control parallelism, by distributing the population of individuals across all available processors. 1