摘要
概念层次树在大规模数据挖掘中已得到广泛应用。在介绍基于概念层次树的数据挖掘算法的基础上,针对已有数值型数据概念提升算法的不足,提出了改进后的算法,并通过数据测试给出两种算法的比较效果和应用实例。
Conception hierarchy tree classifiers have found the widest applicability in large-scale data mining environments.After introduced a data mining algorithm based on conception hierarchy tree.This paper,in the light of the limitations of existed concept assension algorithm to numerical attributes in database,introduces an improved algorithm.Moreover,the result of two algorithm testing on actual data is provided in this paper.
出处
《计算机应用研究》
CSCD
北大核心
2005年第3期61-63,共3页
Application Research of Computers
基金
浙江省自然科学基金资助项目(602096)
关键词
概念层次
数据挖掘
闽值
Conception Hierarchy
Data Mining
Threshold
