A Discretization Algorithm Based on Cultural Immune Algorithm

Abstract

Now more and more researchers pay attention to discretization of the continuous attributes. A hybrid evolutionary system based on immune algorithm and cultural algorithm is proposed for discretization which combines the strengths of evolutionary computing, social computing in this paper. It uses the cultural algorithm framework in which the immune algorithm embedded. Immune algorithm discretizes the continuous data and the cultural algorithm constitutes the commonly accepted beliefs to guide and speed up the search. In addition, a new diversity operator is put forward in order to maintain the diversity of population. Finally, experiments are conducted for extensive performance testing of the new method on several publicly available data sets. The results show that the algorithm has higher convergence speed and less classification errors than many previously known discretization methods.