A New Robust Classifier on Noise Domains: Bagging of Credal C4.5 Trees

Table 11

values of the Nemenyi test about the accuracy on data sets with of added noise.

	Algorithms
21	BA-C4.5-U versus BA-C4.5	0.000034
20	BA-C4.5-U versus BA-CC4.5	0.001194
19	BA-CDT-U versus BA-C4.5	0.002081
18	BA-C4.5-U versus BA-CC4.5-U	0.00305
17	BA-C4.5 versus BA-CDT	0.006311
16	BA-C4.5 versus RF	0.006769
15	BA-CDT-U versus BA-CC4.5	0.029579
14	BA-CDT-U versus BA-CC4.5-U	0.057705
13	BA-CDT versus BA-CC4.5	0.067475
12	BA-CC4.5 versus RF	0.07102
11	BA-CC4.5-U versus BA-CDT	0.120962
10	BA-CC4.5-U versus RF	0.126611
9	BA-C4.5-U versus RF	0.151281
8	BA-C4.5-U versus BA-CDT	0.157987
7	BA-CC4.5-U versus BA-C4.5	0.237833
6	BA-C4.5-U versus BA-CDT-U	0.287015
5	BA-C4.5 versus BA-CC4.5	0.366699
4	BA-CDT-U versus RF	0.711138
3	BA-CDT-U versus BA-CDT	0.728454
2	BA-CC4.5-U versus BA-CC4.5	0.781207
1	BA-CDT versus RF	0.981534