摘要
频繁项集的生成是关联规则挖掘中的关键问题,本文提出了一种基于无向项集图的频繁项集挖掘算法。应用优化算法对病人就诊数据进行挖掘分析,与传统的频繁项集挖掘算法相比,优化算法在执行效率上有明显的提高,对临床实践研究提供有价值的指导意见。
The generation of frequent item sets is the key problem in clinical data mining,thus the frequent item sets mining algorithm is proposed in this paper based on undirected item sets graph.The mining analysis for patients＇ clinical data is carried by optimization algorithm.Compared with the traditional frequent item sets mining algorithms,the optimization algorithm has better execution efficiency,and it has guidance significance for clinical practice research.
关键词
临床数据挖掘
关联规则
频繁项集
无向项集图
Apriori algorithm
clinical data mining
frequent item sets
undirected item sets graph
