Constructing Classification Model with MapReduce
By analyzing the process of classification and MapReduce computing paradigms, it is found that the parallel and distributed computing model in MapReduce is appropriate for constructing classifier model. This paper presents a MapReduce algorithm for parallel and distributed classification, aiming to reduce the computational time in training process on large scale documents. Our experiment shows that the running time of the algorithm is greatly shortened and it is capable for larger scale documents.
classification MapReduce parallel distributed computing model
Xiangxiang Chen Kaigui Wu Changze Wu
Department of Computer Science Chongqing University Chongqing, P.R. China
国际会议
南京
英文
611-615
2010-11-01(万方平台首次上网日期,不代表论文的发表时间)