摘要
提出了一种对原始数据先进行模糊聚类,再提取规则的基于模糊集和粗糙集技术的关联规则挖掘策略,可以在一定程度内减少噪声数据的干扰,消除数据对象中的冗余属性,有利于提高规则挖掘的有效性.
In this paper, a novel association rules mining strategy based on fuzzy set and rough set has been presented. Fuzzy clustering is the first phase, we make use of fuzzy analogue method to realize clustering. Through the clustering, the noise data can be eliminated to a certain extent, which can improve the correctness of result-rules. The second phase is rule-mining ,owing to the attributes reduction, the redundant attributes can be omitted, and the association rules can be educed in the key attributes set.
出处
《江西师范大学学报（自然科学版）》
CAS
北大核心
2005年第1期23-25,30,共4页
Journal of Jiangxi Normal University(Natural Science Edition)
基金
江西省自然科学基金资助项目(0011013).
