Parallel Computation of Fuzzy Rough Approximation Using MapReduce
Fuzzy rough sets model is powerful to deal with hybrid uncertain data.All the existing algorithms are serial and only run on a single computer,thus they can only deal with small data sets.In this work,we focus on MapReduce-based parallel computation of fuzzy rough approximation,which is the foundation for all applications in fuzzy rough sets.A key step in fuzzy rough approximation is fuzzy membership degree computation.Since fuzzy relation does not satisfy transitivity,the basic MapReduce framework cannot be applied to solve this problem.We propose a novel MapReduce model for computing fuzzy relation,which solve the problem by adding another data pipe.Experimental results demonstrate that the proposed model is effective for parallel computation of fuzzy rough approximation.
Fuzzy rough sets MapReduce Parallel computing Hadoop
Si-Yuan JING Kun SHE
School of Computer Science,Leshan Normal University,Leshan,614000,China School of Computer Science & Engineering,University of Electronic Science & Technology of China,Chen
国内会议
杭州
英文
1-4
2014-10-18（万方平台首次上网日期，不代表论文的发表时间）