%0 Journal Article %A KONG Beibei1 %A TANG Xuewen2 %A WANG Weihan1 %T Network traffic classification based on combination of multi-classifiers %D 2013 %R %J Computer Engineering and Applications %P 82-84 %V 49 %N 17 %X Traditionally, in the area of the network traffic classification, there exists a problem that single learning algorithm lacks classification accuracy and is incapable of adapting to the dynamic network environment. Accordingly, it proposes a novel classification approach which is a combination of multi-classifier. This method combines the features of a range of classifiers and then achieves traffic classification by means of majority voting and instance selection. Moreover, comparative experiments show that this method improves the classification accuracy, the generalization performance and the ability to adapt to the dynamic network environment. However, it is worth noting that the method has a larger implement complexity and time complexity than these of single algorithm. %U http://cea.ceaj.org/EN/abstract/article_30880.shtml