桂林电子科技大学学报2016，Vol.36Issue(2)：123-128,6.
基于多层MapReduce的混合网络流量分类特征选择方法
Hybrid network traffic classification feature selection method based on multilayer MapReduce
摘要
Abstract
The traditional feature selection method is only suitable for small-scale datasets and the operating efficiency is low, combining the feature of Filter and Wrapper,a hybrid network traffic classification feature selection method based on multi-layer MapReduce is proposed.In this method,Fisher score is used to preprocess the data,the part of unrelated feature is re-moved and the dimensionality is reduced.Then sequential forward search strategy is adopted,and the best feature for classi-fication is selected constantly by multilayer MapReduce.The experimental results show that this method can not only keep the high classification accuracy,but also reduce the feature selection time.Meanwhile,it can get a nice speedup ratio and in-crease the efficiency of network traffic classification.关键词
特征选择/Fisher score/SFS/MapReduceKey words
feature selection/Fisher score/SFS/MapReduce分类
信息技术与安全科学引用本文复制引用
王勇,龙也,陶晓玲,韦毅..基于多层MapReduce的混合网络流量分类特征选择方法[J].桂林电子科技大学学报,2016,36(2):123-128,6.基金项目
国家自然科学基金(61163058,61363006) （61163058,61363006）
广西可信软件重点实验室开放基金(KX201306) （KX201306）
