摘要
应用关系数据的模糊C 均值算法把数量型属性划分成若干个模糊集 ,提出挖掘区间值关系数据库数量型属性模糊关联规则的算法 .在关系数据的模糊C 均值算法与竞争聚集算法的基础上提出一种新的模糊聚类算法———关系数据的竞争聚集算法 ,并用它来划分数量型属性 .由于关系数据的竞争聚集算法能得到优化的固定的聚类个数 ,因此能挖掘出优化的模糊关联规则 .
The quantitative attributes are partitioned into several fuzzy sets by the relational fuzzy C-means algorithm, and the algorithm for mining quantitative fuzzy association rules in interval valued relational database is provided. A new fuzzy clustering algorithm-relational competitive agglomeration algorithm is provided based on the relational fuzzy C-means algorithm and the competitive agglomeration algorithm, and it is used to divide the quantitative attributes into several fuzzy sets. The optimal fuzzy association rules can be mined due to the optimal fixed clustering number that can be obtained by the relational competitive agglomeration algorithm.
出处
《西安电子科技大学学报》
EI
CAS
CSCD
北大核心
2002年第3期387-391,共5页
Journal of Xidian University
基金
国家自然科学基金资助项目 ( 6 9975 0 2 4)
国家自然科学基金重点资助项目 ( 6 99310 40 )
关键词
数据库
模糊关联规则
区间值
数据控制
C-均值算法
聚集算法
interval values
data mining
relational fuzzy C-means algorithm
relational competitive agglomeration algorithm
association rules
