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Time Series Forecasting On Etth1 192 2
評価指標
MAE
MSE
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
| Paper Title | |||
|---|---|---|---|
| PatchTST/64 | 0.215 | 0.074 | A Time Series is Worth 64 Words: Long-term Forecasting with Transformers |
| SegRNN | 0.208 | 0.068 | SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting |
| FiLM | 0.207 | 0.072 | FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting |
| DLinear | 0.204 | 0.071 | Are Transformers Effective for Time Series Forecasting? |
| PatchMixer | 0.198 | 0.066 | PatchMixer: A Patch-Mixing Architecture for Long-Term Time Series Forecasting |
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