Classification Method by Clonal Selection Algorithm with Immunological Memory and Its Application to Coronary Heart Disease Database

Abstract

The clonal selection principle is used to explain the basic features of an adaptive immune response to a antigenic stimulus. It established the idea that only those cells that recognize the antigens are selected to proliferate and dierentiate. This paper explains a computational implementation of the clonal selection principle that explicitly takes into account the anity maturation of the immune response. The clonal selection algorithm by incorporating receptor editing method, RECSA, has been proposed by Gao. This paper introduce the immune memory cells into RECSA model. In order to verify the eectivness of proposed method, we try to classify MONK's problems and the medical database of Coronary Heart Disease (CHD) database.