AN ATTRIBUTE DISCRETIZATION ALGORITHM BASED ON ROUGH SET AND INFORMATION ENTROPY

摘要：

Attribute discretization is one of the key issues for the Rough Set theory. First, a method is proposed to compute an initial cut points set. The indistinguishable relation of decision tables did not change, and the number of elements in the initial cut points set was reduced. Then, the cut point information entropy was defined to measure the importance of a cut point. Finally, an attribute discretization algorithm based on the Rough Set and information entropy was proposed. The consistence of decision tables did not change, and the mixed decision table was considered, which contains continuous and discrete attributes. The experimental results show that this algorithm is effective and is competent for processing the large-scale datasets.

关键词： Attribute Discretization Rough Set Information Entropy Cut Point

作者: HE LIU DA-YOU LIU XIAO-HU SHI YING GAO

作者单位: College of Computer Science and Technology, Jilin University, Changchun 130012, China Key Laboratory for Symbolic Computation and Knowledge Engineering of Ministry of Education, Changchun 130012, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 206-211

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）