A Parallel Method for Rough Entropy Computation Using MapReduce

Rough set theory has been proven to be a successful computational intelligence tool. Rough entropy is a basic concept in rough set theory and it is usually used to measure the roughness of information set. Existing algorithms can only deal with small data set. Therefore, this paper proposes a method for parallel computation of entropy using MapReduce, which is hot in big data mining. Moreover, corresponding algorithm is also put forward to handle big data set. Experimental results show that the proposed parallel method is effective.