一种基于加权概念格的分类规则提取算法  

A Classification Rule Extraction Algorithm Based on Weighted Concept Lattice

作　　者：孙桂利[1] 张继福[1] 

机构地区：[1]太原科技大学计算机科学与技术学院,太原030024

出　　处：《太原科技大学学报》2011年第5期352-357,共6页Journal of Taiyuan University of Science and Technology

基　　金：山西省自然科学基金(2010011021-2);山西省回国留学人员科研资助项目(2009-77)

摘　　要：加权概念格是针对属性的重要程度,通过引入内涵权值而形成的一种格结构。采用加权概念格作为分类规则提取工具,通过引入加权外延支持度,给出了一种新的分类规则的提取算法CRAAF-WCL。最后,利用恒星光谱数据作为形式背景,实验验证了该算法具有较高的分类效果。Weighted concept lattice is a new concept lattice structure to the importance of attribute by introducing weight into concept lattice＇s intension.In this paper,the weighted concept lattice was used as a classification ruleextraction tool,a new classification rule extraction algorithm CRAAFWCL is presented by introducing concept of the weighted extant support.In the end,experimental results validate that the algorithm has higher classification efficiency by taking the star spectrum data as the formal context.

关 键 词：数据挖掘 加权概念格 分类规则 加权外延支持度 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]