计算机系统应用
計算機繫統應用
계산궤계통응용
APPLICATIONS OF THE COMPUTER SYSTEMS
2013年
2期
108-111
,共4页
朴素贝叶斯%MapReduce%并行化%云计算
樸素貝葉斯%MapReduce%併行化%雲計算
박소패협사%MapReduce%병행화%운계산
Naive Bayes%MapReduce%parallelization%cloud computing
研究朴素贝叶斯算法 MapReduce 的并行实现方法,针对传统单点串行算法在面对大规模数据或者参与分类的属性较多时效率低甚至无力承载大规模运算,以及难以满足人们处理海量数据的需求等问题,本文在朴素贝叶斯基本理论和 MapReduce 框架的基础上,提出了一种基于 MapReduce 的高效、廉价的并行化方法.通过实验表明这种方法在面对大规模数据时能有效提高算法的效率,满足人们处理海量数据的需求.
研究樸素貝葉斯算法 MapReduce 的併行實現方法,針對傳統單點串行算法在麵對大規模數據或者參與分類的屬性較多時效率低甚至無力承載大規模運算,以及難以滿足人們處理海量數據的需求等問題,本文在樸素貝葉斯基本理論和 MapReduce 框架的基礎上,提齣瞭一種基于 MapReduce 的高效、廉價的併行化方法.通過實驗錶明這種方法在麵對大規模數據時能有效提高算法的效率,滿足人們處理海量數據的需求.
연구박소패협사산법 MapReduce 적병행실현방법,침대전통단점천행산법재면대대규모수거혹자삼여분류적속성교다시효솔저심지무력승재대규모운산,이급난이만족인문처리해량수거적수구등문제,본문재박소패협사기본이론화 MapReduce 광가적기출상,제출료일충기우 MapReduce 적고효、렴개적병행화방법.통과실험표명저충방법재면대대규모수거시능유효제고산법적효솔,만족인문처리해량수거적수구.
@@@@This article focused on the realization of the parallelization of Naive Bayes. When it comes to large-scal data or multi-attributes, the traditional singal node algorithm has a low efficiency,or even is unable to host large-scale computing. All of these make the traditional algorithm cannot fit the need to deal with massive data. Therefore, based on the basic theory of Naive Bayes and the framework of MapReduce, this paper proposed a parallelization method of Naive Bayes, which is efficient and cheap.At the end, it is proved by experiments that this method can effectively improve the efficiency of the algorithm so as to meet the need of peoople to deal with massive data.
