重庆邮电大学学报（自然科学版）2011，Vol.23Issue(5)：641-646,6.DOI:10.3979/j.issn.1673-825X.2011.05.028
基于粗糙集理论的两类离散化方法研究
Study on two kinds of discretization methods based on rough set theory
摘要
Abstract
The discretization of continuous attributes is one of the key steps of Data Pretreatment. In practical application, continuous information systems are usually discretized by efficient heuristic algorithms. Herein, two kinds of heuristic data discretization approaches, I. E. Discretization methods respectively based on auxiliary matrixes and information entropy, are thoroughly studied by simulation experiments. Five typical algorithms of each kind are realized and their performances are comprehensively compared by a series of experiments. The experimental results suggest that auxiliary matrix based algorithms are with higher capability, but more complex and time consuming, thus is appropriate for small-scaled continuous systems; and the characteristics of information entropy based algorithms are on the contrary.关键词
粗糙集/离散化/辅助矩阵/信息熵Key words
rough set/discretization/assistant matrix/information entropy分类
信息技术与安全科学引用本文复制引用
张文波..基于粗糙集理论的两类离散化方法研究[J].重庆邮电大学学报（自然科学版）,2011,23(5):641-646,6.基金项目
教育部留学回国人员科研启动基金项目(教外司留[ 2007] 1108号) （教外司留[ 2007] 1108号）
重庆邮电大学科研基金(A2006-05) （A2006-05）
