Research Article
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.
| ā | 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 |
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