A hybrid intelligent data classification algorithm

Xuesong Yan, Wenjing Luo, Qinghua Wu, Victor S. Sheng

Research output: Contribution to journalArticle

9 Scopus citations

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.

Original languageEnglish
Pages (from-to)573-580
Number of pages8
JournalInternational Journal of Wireless and Mobile Computing
Volume6
Issue number6
DOIs
StatePublished - Dec 4 2013

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Keywords

  • Data classification
  • K-nearest neighbour
  • Particle swarm optimisation
  • Weighted k-nearest neighbour

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