基于MapReduce的并行模糊C均值算法-中国云计算.PDFVIP

网络出版时间：2012-04-25 17:21 网络出版地址：/kcms/detail/11.2127.TP1721.057.html Computer Engineering and Applications MapReduce C Yu Qian-qian, Dai Yue-ming , 214122 School of IOT Engineering, Jiangnan University ,Wuxi, Jiangsu 214122, China E-mail: cheeryu87@ Parallel fuzzy C-means algorithm based on MapReduce Abstract :Fuzzy C-means is an important soft-clustering algorithm, but with the increased amount of data the time complexity will be increased. In this paper, a parallel fuzzy C-means algorithm based on the MapReduce is proposed. The fuzzy C-means algorithm is redesigned to meet the MapReduce programming model. The membership degree of data set to the center is computed in parallel, and the new cluster center is re-calculated, so that the higher calculating efficiency of processing large amount of data can be got. The experiments shown the parallel fuzzy C-means algorithm based on the MapReduce has the advantages of both high speed up and good scalability. Key words: fuzzy C-means; parallel computing; MapReduce; data mining; cloud computing C C MapReduce C C MapReduce key/value C MapReduce C C MapReduce A TP301 1 [4] Apache HadoopMapReduce K-means Greedy C Agglomerative Expectation Maximization C Apache HadoopMapReduce MapReduce C C [1,2] [3] MapReduce C Intel Parallel Amplifier C C : (1987 ),,;(1964 ),,