Research Article
EBOC: Ensemble-Based Ordinal Classification in Transportation
Table 4
The comparison of RandomTree based ordinal and ensemble learning methods in terms of classification accuracy.
| Dataset | Random | Ord.Random | Ada.Ord. | Bag.Ord. | Tree | Tree | RandomTree | RandomTree | (%) | (%) | (%) | (%) |
| Auto MPG | 77.64 | 81.66 | 82.66 | 81.41 |
| Automobile | 76.59 | 74.63 | 83.41 | 84.88 |
| Bike Sharing | 80.07 | 80.56 | 86.98 | 87.73 |
| Car Evaluation | 83.16 | 85.94 | 97.22 | 95.83 |
| Car Sale Advertisements | 82.38 | 82.12 | 83.90 | 86.34 |
| NYS Air Passenger Traffic | 86.11 | 86.17 | 85.61 | 86.49 |
| Road Traffic Accidents (2017) | 78.76 | 78.44 | 82.21 | 84.48 |
| SF Air Traffic Landings Statistics | 97.38 | 97.43 | 98.93 | 98.83 |
| SF Air Traffic Passenger Statistics | 89.22 | 89.27 | 89.05 | 89.17 |
| Smart City Traffic Patterns | 82.26 | 82.79 | 84.72 | 85.91 |
| Statlog (Vehicle Silhouettes) | 70.92 | 65.60 | 76.71 | 76.00 |
| Traffic Volume Counts (2012-2013) | 82.96 | 83.45 | 89.77 | 89.69 |
| Average | 82.29 | 82.34 | 86.76 | 87.23 |
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