摘要
In data mining, traditional clustering techniques are not so effective as hoped. The large-scale databases, the disagreements in variable’s measurement levels, and the exhausting distance matrix operation, are the three main obstacles.By using roughset theory, we introduced a new clustering approach in large-scale data analysis without using geometry distance measurements.
In data mining, traditional clustering techniques are not so effective as hoped. The large-scale databases, the disagreements in variable＇s measurement levels, and the exhausting distance matrix operation, are the three main obstacles. By using roughset theory, we introduced a new clustering approach in large-scale data analysis without using geometry distance measurements.
出处
《统计研究》
CSSCI
北大核心
2005年第8期56-60,共5页
Statistical Research
基金
2004年国家教育部新世纪优秀人才支持计(NCET040608)
国家统计局科研计划项目(LXZ0409)资助。
