An Artificial Immune Based Incremental Data Clustering Algorithm

Abstract:

An improved resource limited artificial immune algorithm is proposed, which is applied to the incremental data clustering. The algorithm adopts an improved function of stimulation level, allowing the system to distributing resources more reasonably. And the algorithm introduces the immune response model, simulating the initial response and the secondary response. Through simulation experiments on the UCI data sets, and comparison with the artificial immune based influential incremental clustering algorithms, it shows that the algorithm is effective, can extract data characteristics, and increases the clustering accuracy and data compression rate.

• Periodical: Applied Mechanics and Materials (Volumes 256-259)
• Pages: 2935-2938
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.256-259.2935
• Online since: December 2012
• Authors: Xin Xiao
• Keywords: Artificial Immune, Data Clustering, Immune Network, Immune Response, Incremental Clustering

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