A New Approach of Self-adaptive Discretization to Enhance the Apriori Quantitative Association Rule Mining

Apriori algorithm was widely applied in association rule mining. Generally, we have to specify different ranges manually to discretize numeral fields to nominal fields, which may weaken the result due to unfit partitions. This paper introduced an approach to make discretized partitions in a self adaptive way to enhance the numeral quantitative association rule mining result.