计算机应用研究2016，Vol.33Issue(11)：3215-3218,4.DOI:10.3969/j.issn.1001--3695.2016.11.004
基于 Hadoop平台的SVM＿WNB分类算法的研究
Research of SVM_WNB classification algorithm based on Hadoop platform
摘要
Abstract
SVM algorithm and naive Bayesian classification algorithm are the good performance of classification algorithm for complex data classification.However,they also have significant drawbacks so their classification are influenced and the tradi-tional data mining classification algorithm can not meet the need of mass data processing.To solve these problems,this paper analyzed traditional naive Bayesian classification algorithm and raised improvement suggestions for it,brought forward the SVM_WNB classification algorithm.Then it conducted a parallelization processing on Hadoop cloud platform so that it could process mass data.Finally,through experimental verification,the new algorithm has obvious improvement in terms of its accuracy and efficiency.It can be concluded that the algorithm can be applied to large data classification,and will play a significant effect.关键词
大数据/数据挖掘/SVM_WNB算法/Hadoop云平台/并行化Key words
big data/data mining/SVM_WNB algorithm/Hadoop cloud platform/parallelization分类
信息技术与安全科学引用本文复制引用
黄刚,李正杰..基于 Hadoop平台的SVM＿WNB分类算法的研究[J].计算机应用研究,2016,33(11):3215-3218,4.基金项目
国家自然科学基金资助项目 （）
