摘要
通过加权平均算法(ML_TWA)发现多层关联规则.该算法针对现有多层关联规则挖掘中存在阈值定义不合理的情况,依据多层数据的特点,提出了一种加权平均阈值估计方法,来提高挖掘效率和结果的准确性.实验结果证明这种算法是有效的.
Association rules mining is one of the important research fields in data mining. In this paper we present a weighted average method named MLTWA to discovery muhi-level association rules. It put forward a heuristic user-defined method which based on the characteristic of multi-level data to overcome the drawbacks caused by the unreasonable method of defining threshold. So the precision and efficiency of mining association rules is improved,The experimental results show that the efficiency of the algorithm for large databases.
出处
《河南科学》
2007年第6期988-991,共4页
Henan Science
基金
河南省高校杰出科研人才创新工程项目(2007KYCX018)
关键词
概念分层
关联规则
加权平均
数据挖掘
concept hierarchies
association rule
weighted average
data mining
