Mapper Association Rule Reducer Mining Method (MARRMM) for the Diagnosis of Heart Disease Using Hesitation Rule Set

Abstract

Association rule is one of the primary tasks in data mining that discovers correlations among items in a transactional database. The majority of vertical and horizontal association rule mining algorithms have been developed to improve the frequent items discovery step which necessitates high demands on training time and memory usage particularly when the input database is very large. In this paper, in the third work, a novel hesitation rule generation method has proposed by blending the Map Reduce concept and Association Rule Mining. In this Mapper Association Rule Reducer Mining method has proposed to generate the hesitation rule set for giving the appropriate medication to the patient who are considered as not getting heart disease.