基于分布式的关联规则算法在医疗数据挖掘中的应用
Application of Association Rules Algorithm Based on Distributed in Medical Data Mining
李晓楠 1马元吉 2肖川3
作者信息
- 1. 四川大学计算机学院，成都 610065
- 2. 四川大学华西医院，成都 610041
- 3. 四川大学华西公共卫生学院，成都 610041
- 折叠
摘要
通过研究基于Hadoop平台的map/reduce思想，针对关联规则算法Apriori算法提出其在分布式平台下的改进算法，利用分布式化的Apriori算法对居民体检中发现的乙肝患者疾病数据进行分析挖掘，主要建立乙肝阳性和其他健康指标间的关联规则。实验结果证明关联规则算法Apriori在医疗数据挖掘中的有效性和高效性。
Abstract
By researching on the map/reduce theory based on Hadoop distributed system, for Apriori algorithm, which is a kind of association rules algorithm, puts forward the improved algorithm in a distributed platform. Uses distributed data Apriori algorithm to analyze data of disease patients with hepatitis B which is found in healthy examination. The purpose is to establish association rules between HBV-positive and other health indicators. The results prove that the association rule mining algorithms on medical data is effectiveness and efficiency.
关键词
分布式/Apriori算法/医疗数据/数据挖掘Key words
Distributed/Apriori Algorithm/Medical Data/Data Mining引用本文复制引用
基金项目
国家重大科技专项(2012ZX10004-901)
四川省科技支撑计划项目(2013SZ0002)
四川省科技支撑计划项目(2014SZ0109)
出版年
2015
NETL
NSTL
维普
万方数据