The Community for Technology Leaders
2013 IEEE 13th International Conference on Data Mining Workshops (2006)
Hong Kong, China
Dec. 18, 2006 to Dec. 22, 2006
ISBN: 0-7695-2702-7
pp: 120-124
Huo-Wang Chen , National Laboratory for Parallel and Distributed Processing, Changsha 410073 China
Jian Wen , National Laboratory for Parallel and Distributed Processing, Changsha 410073 China
Li-Juan Zhang , National Laboratory for Parallel and Distributed Processing, Changsha 410073 China
Zhou-Jun Li , Beihang University, Beijing 100083 China
ABSTRACT
In this article we describe a method for selecting informative genes from microarray data. The method is based on clustering, namely, it first find similar genes, group them and then select informative genes from these groups to avoid redundancy. A new gene similarity measure based on Grey Relational Analysis (GRA), called Grey Relational Grade (GRG), is used in clustering. Experiments on three public data sets demonstrate the effectiveness of our method.
INDEX TERMS
null
CITATION
Huo-Wang Chen, Jian Wen, Li-Juan Zhang, Zhou-Jun Li, "Minimum Redundancy Gene Selection Based on Grey Relational Analysis", 2013 IEEE 13th International Conference on Data Mining Workshops, vol. 00, no. , pp. 120-124, 2006, doi:10.1109/ICDMW.2006.108
93 ms
(Ver 3.3 (11022016))