摘要
文章介绍了粗糙集的发展现状和相关概念,指出特征选择是运用粗糙集理论进行数据挖掘中最重要的一个环节;利用已求得的正区域和限制正域使处理数据的范围不断缩小从而减少求约简的时间,最后通过对形状进行知识约简,验证了用这个方法进行形状分析是可行的。
This paper introduces the development situation of rough set and the related concepts,and points out that the feature selection is the most important step in using rough set theory for data mining.The obtained and restricted positive regions are used to narrow the scope of data processing so as to reduce the reduction time.Finally,the knowledge reduction on shape is carried out,which confirms that this method is feasible for shape analysis.
出处
《合肥工业大学学报（自然科学版）》
CAS
CSCD
北大核心
2012年第3期334-336,共3页
Journal of Hefei University of Technology：Natural Science
基金
国家自然科学基金资助项目(60673028)
关键词
形状分析
特征选择
限制正域
启发式算法
shape analysis
feature selection
restrictive positive region
heuristic algorithm
