A Discretization Algorithm That Keeps Positive Regions of All the Decision Classes

摘要：

　　Most of the existing discretization methods such as k-interval discretization, equal width and equal frequency methods do not take the dependencies of decision attributes on condition attributes into account.In this paper, we propose a discretization algorithm that can keep the dependencies of the decision attribute on condition attributes, or keep the positive regions of the partition of the decision attribute.In the course of inducing classification rules from a data set, keeping these dependencies can achieve getting the set of the least condition attributes and the highest classification precision.

作者: Feng Honghai Liu Baoyan He LiYun Yang Bingru Li Yueli

作者单位: Hebei Agricultural University,071001 Baoding,China;University of Science and Technology Beijing,1000 China Academy of Traditional Chinese Medicine,100700 Beijing,China University of Science and Technology Beijing,100083 Beijing,China Hebei Agricultural University,071001 Baoding,China

会议类型: 国内会议

会议名称: ”数字化中医信息系统“临床术语本体研究专家研讨会

会议地点: 北京

会议语种:英文

页码: 1029-1036

在线出版日期: 2014-09-01（万方平台首次上网日期，不代表论文的发表时间）