Application of committee kNN classifiers for gene expression profile classification
by Manik Dhawan, Sudarshan Selvaraja, Zhong-Hui Duan
International Journal of Bioinformatics Research and Applications (IJBRA), Vol. 6, No. 4, 2010

Abstract: In this study, we develop a two-class classification system based on a committee of k-Nearest Neighbour (kNN) classifiers. The system includes a sequence of simple data preprocessing steps. Each committee consists of 5 kNN classifiers of different architectures. Each classifier on the committee takes in a different set of features. The classification system is then applied to a set of microarray gene expression profiles from leukaemia patients. We show that the system can be effectively used for classifying microarray gene expression data. The results demonstrate the committee approach consistently outperforms individual kNN classifiers in terms of both classification accuracy and stability.

Online publication date: Mon, 11-Oct-2010

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 Bioinformatics Research and Applications (IJBRA):
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