基于DT-KSVM的业务感知算法

doi:10.11959/j.issn.1000-0801.2015227

Abstract

Abstract:

A novel service-aware method based on decision tree kernel support vector machine（DT-KSVM） algorithm was proposed.A service-aware model was developed by using ReliefF algorithm to extract service characteristics,and proposing the separable degree between samples to simply the service-aware process.Through experiment comparison between this proposed model and traditional one-versus-one SVM method,it is shown that the proposed method has a better service-aware accuracy and time performance.

Key words: support vector machine, decision tree, service-aware

Hao Dong,Hua Qu,Jihong Zhao,Liangjun Chen,Huijun Dai. Service-Aware Algorithm Based on DT-KSVM[J]. Telecommunications Science, 2015, 31(11): 67-71.

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References 10

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排序前			排序后
序号	类别	可分度	序号	类别	可分度
1	Gnutella	4.911 687 8E12	1	Thunder	1.326 261 36E13
2	eDonkey	7.976 978 5E12	2	eDonkey	7.976 978 5E12
3	Thunder	1.326 261 36E13	3	BitTorrent	7.700 031 2E12
4	KaZaA	5.171 715 2E12	4	KaZaA	5.171 715 2E12
5	BitTorrent	7.700 031 2E12	5	Gnutella	4.911 687 8E12

分类面	数据集	C	g
SVM1	Originals.libsvm	32 768	0.125
SVM2	Original0s.libsvm	8 192	0.031 25
SVM3	Original1s.libsvm	8 192	0.5
SVM4	Original11s.libsvm	2	0.5

业务类型	识别数目	实际数目	识别数/实际数	召回率
Gnutella	371	390	95.1%	94.6%（369/390）
eDonkey	414	430	96.2%	95.8%（412/430）
Thunder	387	400	96.7%	96.7%（387/400）
KaZaA	440	420	104.7%	95.2%（400/420）
BitTorrent	482	454	106.1%	96.9%（440/454）

算法类别	准确率
1vs1	93.97%
DT-KSVM	96.08%

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Service-Aware Algorithm Based on DT-KSVM

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