一种新的基于人工免疫系统的增量聚类算法

Xianghua Li, Tianyang Lu, Zhengxuan Wang, Chao Gao
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引用次数: 6

摘要

虽然提出了多种聚类算法,但对增量聚类的研究却很少。受人工免疫系统的启发,作者将其应用于增量聚类,提出了一种新的增量聚类算法ICAIS。该算法主要利用了适应性免疫系统的免疫应答机制。初级免疫反应对应于形成新的群集。二级免疫反应对应于识别属于现有集群的数据。实验表明,ICAIS在识别新图案方面具有优势,效果较好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ICAIS: A Novel Incremental Clustering Algorithm Based on Artificial Immune Systems
Although many kinds of clustering algorithms are proposed, there has been much less work on the incremental clustering. Inspired by the artificial immune systems, the authors apply it to the incremental clustering, propose a novel incremental clustering algorithm called ICAIS. The algorithm mainly uses the mechanism of immune response of the adaptive immune system. The primary immune response corresponds to forming the new clusters. The secondary immune response corresponds to recognizing the data belonging to the existed clusters. The experiments show that ICAIS has advantages in recognizing new pattern, the effect is better.
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