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

Table 13

values of the Nemenyi test about the accuracy on data sets with 30% of added noise.

	Algorithms
21	BA-C4.5-U versus BA-CC4.5	0
20	BA-C4.5-U versus BA-CDT	0
19	BA-CC4.5 versus RF	0
18	BA-CDT versus RF	0
17	BA-CDT-U versus BA-CC4.5	0
16	BA-C4.5-U versus BA-CC4.5-U	0
15	BA-CDT-U versus BA-CDT	0
14	BA-CC4.5-U versus RF	0
13	BA-C4.5-U versus BA-C4.5	0.000003
12	BA-C4.5 versus BA-CC4.5	0.000038
11	BA-C4.5 versus RF	0.000101
10	BA-C4.5 versus BA-CDT	0.000111
9	BA-CDT-U versus BA-CC4.5-U	0.000668
8	BA-CC4.5-U versus BA-CC4.5	0.005479
7	BA-C4.5-U versus BA-CDT-U	0.008911
6	BA-CC4.5-U versus BA-CDT	0.01164
5	BA-CDT-U versus BA-C4.5	0.039403
4	BA-CDT-U versus RF	0.067475
3	BA-CC4.5-U versus BA-C4.5	0.179454
2	BA-C4.5-U versus RF	0.431313
1	BA-CDT versus BA-CC4.5	0.799032