关键词: 阴性选择算法, 模式分类, 克隆选择, negative-selection algorithm, pattern classification, clonal selection

Abstract: A negative selection algorithm for multi-class pattern classification problems named CS-NSA was proposed. The algorithm used clonal selection mechanism to implement self-adaptive learning of detectors and adopted detector trimming mechanism to tackle the over-fitting problem in multi-class classification. This mechanism enhanced the generalization capability of the detectors. The results of comparative experiments show that the proposed algorithm exhibits higher classifying accuracy than that of AIRS, a famous artificial immune classifier.