Research Article
EBOC: Ensemble-Based Ordinal Classification in Transportation
Table 3
The comparison of C4.5 based ordinal and ensemble learning methods in terms of classification accuracy.
| Dataset | C4.5 | Ord.C4.5 | Ada.Ord.C4.5 | Bag.Ord.C4.5 | (%) | (%) | (%) | (%) |
| Auto MPG | 80.40 | 80.90 | 83.67 | 81.91 |
| Automobile | 81.95 | 66.34 | 84.39 | 73.66 |
| Bike Sharing | 87.75 | 87.72 | 89.29 | 89.79 |
| Car Evaluation | 92.36 | 92.19 | 98.73 | 94.27 |
| Car Sale Advertisements | 83.65 | 81.09 | 83.82 | 85.00 |
| NYS Air Passenger Traffic | 84.91 | 85.42 | 86.05 | 86.81 |
| Road Traffic Accidents (2017) | 85.29 | 85.29 | 81.03 | 84.38 |
| SF Air Traffic Landings Statistics | 98.74 | 98.31 | 99.37 | 98.69 |
| SF Air Traffic Passenger Statistics | 90.68 | 90.82 | 90.41 | 91.43 |
| Smart City Traffic Patterns | 85.66 | 85.98 | 85.07 | 86.94 |
| Statlog (Vehicle Silhouettes) | 72.46 | 68.91 | 78.13 | 74.82 |
| Traffic Volume Counts (2012-2013) | 88.36 | 88.12 | 89.77 | 89.10 |
| Average | 86.02 | 84.26 | 87.48 | 86.40 |
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