Rough sets base associative classification rules extraction from big data

Abstract

Big Data is a current burning challenge for the data analytics research community. Many conventional data analytics techniques have been extended to the MapReduce framework to process Big Data. But in our literature review, we find that for the MapReduce system there is an absolute lack of rough set-based technique. To facilitate this and recognize the importance of the rule-based classification techniques, we suggest a rough-set associative classification rules extraction process for the MapReduce framework. The implementation and evaluation of the Big Data Standard data set demonstrated the efficiency of our suggested approach.