Bus Occupancy Prediction Global setting (test)
4.86RMSELightGBM
Evaluation results
| Method | Links | |||||
|---|---|---|---|---|---|---|
| LightGBMModel Architecture=Global, Features=ID Features, Experiments=142026.04 | 4.86 | 3.25 | 2,910,000,000 | 75.29 | 74.67 | |
| CatBoostModel Architecture=Global, Features=ID Features, Experiments=142026.04 | 4.9 | 3.28 | 2,850,000,000 | 75.89 | 76.36 | |
| RandomForestModel Architecture=Global, Features=ID Features, Experiments=142026.04 | 4.98 | 3.32 | 2,760,000,000 | 77.14 | 75.93 | |
| XGBoostModel Architecture=Global, Features=ID Features, Experiments=142026.04 | 5.02 | 3.38 | 2,960,000,000 | 77.85 | 77.67 | |
| LinearRegressionModel Architecture=Global, Features=ID Features, Experiments=142026.04 | 525.45 | 26.27 | 44,100,000,000 | 8,320 | 78 |