Time Series Forecasting on Traffic (MSE, MAE, DTW, TDI)
0.429MSETime-LLM
Evaluation Results
| Method | Links | ||||
|---|---|---|---|---|---|
| Time-LLMlearning_protocol=Few-shot, training_data=10%2026.05 | 0.429 | 0.306 | 6.925 | 0.012 | |
| PatchTSTlearning_protocol=Few-shot, training_data=10%2026.05 | 0.43 | 0.305 | 6.96 | 0.012 | |
| STaTlearning_protocol=Few-shot, training_data=10%2026.05 | 0.435 | 0.311 | 6.87 | 0.013 | |
| GPT4TSlearning_protocol=Few-shot, training_data=10%2026.05 | 0.44 | 0.31 | 7.218 | 0.012 | |
| DLinearlearning_protocol=Few-shot, training_data=10%2026.05 | 0.447 | 0.313 | 7.276 | 0.012 | |
| Time-VLMlearning_protocol=Few-shot, training_data=10%2026.05 | 0.484 | 0.357 | 7.861 | 0.013 | |
| TimeCMAlearning_protocol=Few-shot, training_data=10%2026.05 | 0.559 | 0.383 | 6.657 | 0.016 | |
| FEDformerlearning_protocol=Few-shot, training_data=10%2026.05 | 0.663 | 0.425 | 9.334 | 0.016 | |
| TimesNetlearning_protocol=Few-shot, training_data=10%2026.05 | 0.951 | 0.535 | 8.817 | 0.014 | |
| Stationarylearning_protocol=Few-shot, training_data=10%2026.05 | 1.453 | 0.815 | 8.158 | 0.014 |