%0 Journal Article
%T Research on P2P Traffic Identification Based on K-means Ensemble and SVM<br>基于K均值集成和SVM的P2P流量识别研究
%A 刘三民
%A 孙知信
%A 刘余霞
%J 计算机科学
%D 2012
%I 
%X A P2P traffic identification model was constructed by the combination of K-means ensemble and support vector machine. It owns high accuracy, stability and overcomes complexity of cluster model. Firstly, the three base clusterer was formed by few labeled sample, and then the each cluster's label was assigned by MAP. The unlabeled sample's label is the same with the closest cluster. Identification model based on SVM was built by new sample set. hhe model makes the best of ensemble learning's stability and SVM's generalization ability, theoretical analysis and result demon-strate its feasibility.
%K Traffic identification
%K Support vector machines
%K K-means
%K Ensemble learning<br>流量识别，支持向量机，K均值，集成学习
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=5C6A9FB29B9932209E96706EE0ECD0C2&yid=99E9153A83D4CB11&vid=7C3A4C1EE6A45749&iid=E158A972A605785F&sid=D997634CFE9B6321&eid=2B8137526B8012E5&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=0