Redundant Feature Selection Based on Hybrid GA and BPSO

摘要：

Redundant Feature selection is an important topic in the field of bioinformatics. This paper proposes a novel algorithm on Redundant Feature Selection Based on Hybrid GA and BPSO(RFS-GSO), which tries to find a compact feature subset with great predictive ability. Compared with the previous works, RFS-GSO measures the redundancy of feature set by the maximum feature inter-correlation, which is more reasonable than those by the averaged inter-correlation. The outstanding performance of RFS-GSO has been examined by the experiments on several real world microarray data sets.

关键词： feature selection redundant feature hybrid GA and BPSO

作者: Su-Fen Chen

作者单位: College of Information Engineering Nanchang Institute of Technology Nanchang 330099, China

会议类型: 国际会议

会议名称: 2011 International Conference on Information and Computer Networks(ICICN 2011)(2011年信息与计算机网络国际会议)

会议地点: 贵阳

会议语种:英文

页码: 414-418

在线出版日期: 2011-01-26（万方平台首次上网日期，不代表论文的发表时间）