Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets
M. Martínez-Ballesteros, Jaume Bacardit, Alicia Troncoso, José C. Riquelme · Integrated Computer-Aided Engineering · 2015
Association rule mining is a well-known methodology to discover significant and apparently hidden relations among attributes in a subspace of instances from datasets. Genetic algorithms have been extensively used to find interesting association rules