Research Article
A New Robust Classifier on Noise Domains: Bagging of Credal C4.5 Trees
Table 14
values of the Nemenyi test about the accuracy on data sets with 40% of added noise.
| | ā | Algorithms | |
| | 21 | BA-C4.5-U versus BA-CC4.5 | 0 | | 20 | BA-CC4.5 versus RF | 0 | | 19 | BA-C4.5-U versus BA-CDT | 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 versus BA-CC4.5 | 0.000001 | | 12 | BA-C4.5 versus BA-CDT | 0.000056 | | 11 | BA-C4.5-U versus BA-C4.5 | 0.000056 | | 10 | BA-CDT-U versus BA-CC4.5-U | 0.000161 | | 9 | BA-C4.5 versus RF | 0.000177 | | 8 | BA-CC4.5-U versus BA-CC4.5 | 0.00178 |
| | 7 | BA-C4.5-U versus BA-CDT-U | 0.031355 | | 6 | BA-CC4.5-U versus BA-CDT | 0.033222 | | 5 | BA-CC4.5-U versus BA-C4.5 | 0.057705 | | 4 | BA-CDT-U versus BA-C4.5 | 0.060822 | | 3 | BA-CDT-U versus RF | 0.060822 | | 2 | BA-CDT versus BA-CC4.5 | 0.319611 | | 1 | BA-C4.5-U versus RF | 0.781207 |
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