A Novel Immune Algorithm for Supervised Classification Problem

Abstract

This article presents a novel immune algorithm for a solution of supervised classification problem .The algorithm is based on the risk model, the use of dangerous and hazardous signal mechanism, the risk by assessing the Antigen to the signal classification; and use of antibody-Antigen interactions learning mechanisms to make antibodies have strong populations of adaptive learning capacity. Simulation results show that the algorithm have good classification results and learning performance compared with other traditional algorithm.