A hybrid intelligent data classification algorithm

Authors:
Xuesong Yan;Wenjing Luo;Qinghua Wu;Victor S. Sheng
Affiliations:
School of Computer Science, China University of Geosciences, Wuhan, Hubei 430074, China;School of Computer Science, China University of Geosciences, Wuhan, Hubei 430074, China;Hubei Provincial Key Laboratory of Intelligent Robot, School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan, Hubei 430073, China;Department of Computer Science, University of Central Arkansas, Conway, AR 72035, USA
Venue:
International Journal of Wireless and Mobile Computing
Year:
2013

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Abstract

k-Nearest Neighbour KNN is one of the most popular algorithms for pattern recognition and data classification, but the traditional KNN classification method has some disadvantages. In this paper, aim at the KNN classification method's limitation, we proposed a hybrid intelligent classification algorithm. This novel algorithm combined the particle swarm optimisation algorithm and weighted KNN algorithm to improve classification performance. The experimental results show that our proposed algorithm outperforms the traditional KNN method with greater accuracy.