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

Table 23

AUC results of WeChat text traffic dataset.

Pkts #	Bayes Net	N/Bayes	SMO	Adaboost	Bagging	OneR	Part	Hoeffbing	C4.5	R/forest	Average
2	0.666	0.833	0.833	0.833	0.666	0.666	0.833	0.916	0.833	1.000	0.807
3	0.666	0.944	0.888	0.833	0.777	0.666	0.888	0.944	0.888	1.000	0.849
4	0.916	0.833	0.833	0.833	0.916	0.666	1.000	0.916	1.000	1.000	0.891
5	0.900	0.933	0.866	0.833	0.933	0.666	1.000	0.933	1.000	1.000	0.906
6	0.888	0.916	0.861	0.833	0.944	0.833	1.000	0.916	0.909	1.000	0.910
7	0.880	0.928	0.880	0.833	0.952	0.833	1.000	0.928	1.000	1.000	0.923
8	0.875	0.916	0.875	0.833	0.958	0.875	1.000	0.916	1.000	1.000	0.924
9	0.870	0.907	0.870	0.833	0.944	0.870	0.981	0.907	0.981	1.000	0.916
10	0.866	0.916	0.866	0.850	0.950	0.883	0.983	0.883	0.966	1.000	0.916
11	0.863	0.906	0.878	0.848	0.939	0.893	0.984	0.893	0.969	0.985	0.915
12	0.861	0.916	0.875	0.847	0.930	0.944	0.986	0.888	0.972	1.000	0.921
13	0.974	0.897	0.871	0.846	0.935	0.935	0.987	0.900	0.974	1.000	0.931
14	0.880	0.892	0.857	0.833	0.976	0.916	0.976	0.880	0.976	1.000	0.918
15	0.933	0.888	0.655	0.833	0.922	0.922	0.966	0.866	0.966	1.000	0.895
16	0.927	0.875	0.812	0.843	0.927	0.916	0.979	0.864	0.947	1.000	0.909
17	0.911	0.754	0.705	0.823	0.911	0.911	0.960	0.735	0.941	1.000	0.865
18	0.916	0.759	0.703	0.814	0.907	0.907	0.925	0.759	0.944	1.000	0.863
19	0.912	0.771	0.710	0.807	0.894	0.929	0.947	0.771	0.947	1.000	0.868
20	0.908	0.758	0.708	0.808	0.933	0.925	0.941	0.766	0.941	1.000	0.868