A hybrid intelligent data classification algorithm
by Xuesong Yan; Wenjing Luo; Qinghua Wu; Victor S. Sheng
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 6, No. 6, 2013

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.

Online publication date: Thu, 16-Oct-2014

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Wireless and Mobile Computing (IJWMC):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com