A Map Reduce Framework for Identifying Association Rules Between Clinical Traits of Asthma Poorani S.1, Balasubramanie P.2,* 1Assistant Professor, Kongu Engineering College, Perundurai, Erode, Tamil Nadu, India 2Professor, Kongu Engineering College, Perundurai, Erode, Tamil Nadu, India *Corresponding Author: P. Balasubramanie, Professor, Kongu Engineering College, Perundurai, Erode, Tamil Nadu, India, Phone: 9443942365, Email: pbalu_20032001@yahoo.co.in
Online published on 19 August, 2019. Abstract Asthma is one of the major wide spread and continual conditions worldwide. Ecological features may play vital roles in asthma. In data mining, association rule mining is the appropriate algorithm to identify the relationship between different features of a dataset. Big data Analysis helps in preventing the disease and detecting the disease in advance. MapReduce helps in reducing the time complexity of big data. In this paper, we propose a MapReduce framework with association rule mining technique to find the clinical traits of asthma. Top Keywords Asthma, Association Rule Mining, Clinical Traits, Apriori Algorithm, Data Mining, Map Reduce, Big Data. Top |