A Comparative Analysis of Discretization Algorithms for Data Mining

摘要：

In this paper, four kinds of typical discretization algorithms were comparatively analyzed from two aspects with examples, one referred to the variable quality of classification and accuracy of approximation under different parameter, the other was the similarity degrees between reducted variable sets and the original variable set. On determination of reducted variable sets, the reduction was regarded as multi-objective optimization problem, which was solved by the genetic algorithm, and the optimal reducted variable sets were found through including degrees. Finally, the consistent conclusion on preference of discretization algorithms was gained.

作者: Xie Ming Xiao Xinping

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Grey System and Intelligent Services(2009 IEEE灰色系统与服务科学国际会议)

会议地点: 南京

会议语种:英文

页码: 1434-1438

在线出版日期: 2009-10-20（万方平台首次上网日期，不代表论文的发表时间）