Effective Packet Number for 5G IM WeChat Application at Early Stage Traffic Classification

Table 24

AUC results of WeChat video traffic dataset.

Pkts #	Bayes Net	N/Bayes	SMO	Adaboost	Bagging	OneR	Part	Hoeffbing	C4.5	R/forest	Average
2	0.666	0.800	0.833	0.833	0.666	0.666	0.666	0.833	0.666	0.833	0.746
3	0.666	0.777	0.611	0.666	0.611	0.611	0.666	0.722	0.666	0.777	0.677
4	0.708	0.708	0.791	0.791	0.708	0.666	0.833	0.791	0.833	0.833	0.766
5	0.766	0.866	0.733	0.866	0.800	0.633	0.933	0.900	0.933	0.866	0.829
6	0.750	0.805	0.861	0.833	0.722	0.666	0.888	0.861	0.888	0.861	0.813
7	0.809	0.857	0.738	0.928	0.928	0.642	0.904	0.928	0.904	0.928	0.856
8	0.812	0.854	0.791	0.916	0.854	0.666	0.895	0.958	0.895	0.958	0.859
9	0.833	0.796	0.740	0.851	0.814	0.648	0.944	0.870	0.944	0.888	0.832
10	0.850	0.916	0.800	0.883	0.85	0.666	0.950	0.966	0.950	0.916	0.874
11	0.878	0.833	0.772	0.924	0.893	0.742	0.954	0.909	0.954	0.954	0.881
12	0.944	0.888	0.805	0.930	0.888	0.833	0.958	0.958	0.958	0.958	0.912
13	0.846	0.871	0.692	0.897	0.910	0.871	0.948	0.884	0.948	0.923	0.879
14	0.845	0.892	0.809	0.928	0.928	0.880	0.952	0.976	0.952	0.964	0.912
15	0.844	0.900	0.811	0.855	0.922	0.844	0.944	0.955	0.944	0.966	0.898
16	0.968	0.885	0.802	0.875	0.854	0.864	0.979	0.958	0.979	0.958	0.912
17	0.960	0.901	0.705	0.911	0.911	0.852	0.980	0.960	0.980	0.980	0.914
18	0.972	0.907	0.814	0.944	0.925	0.925	0.981	0.962	0.981	0.972	0.938
19	0.982	0.921	0.815	0.938	0.973	0.938	1.000	0.964	1.000	1.000	0.953
20	0.975	0.975	0.808	0.925	0.966	0.975	1.000	0.958	1.000	1.000	0.958