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Time Series Forecasting
벤치마크
Time Series Forecasting on ETTm2 (96) Multivariate
18개 결과 ·
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MSE
낮을수록 좋음
0.153
0.16
0.167
0.174
0.181
2023-05
2026-11
RLinear — 0.164 (2023-05-18)
RLinear — 0.164 (2023-05-18)
SCNN — 0.163 (2023-05-22)
SCNN — 0.163 (2023-05-22)
TSMixer — 0.164 (2023-06-14)
TSMixer — 0.164 (2023-06-14)
MoLE-DLinear — 0.168 (2023-12-11)
MoLE-DLinear — 0.168 (2023-12-11)
TEFN — 0.181 (2024-05-10)
TEFN — 0.181 (2024-05-10)
PRformer — 0.162 (2024-08-20)
PRformer — 0.162 (2024-08-20)
LTBoost (drop_last=false) — 0.156 (2024-10-21)
LTBoost (drop_last=false) — 0.156 (2024-10-21)
DiPE-Linear — 0.162 (2024-11-26)
DiPE-Linear — 0.162 (2024-11-26)
xPatch — 0.153 (2024-12-23)
xPatch — 0.153 (2024-12-23)
RLinear — 0.164 (2023-05-18)
SCNN — 0.163 (2023-05-22)
PRformer — 0.162 (2024-08-20)
LTBoost (drop_last=false) — 0.156 (2024-10-21)
xPatch — 0.153 (2024-12-23)
2023-05-18 — RLinear: MSE 0.164
2023-05-22 — SCNN: MSE 0.163
2024-08-20 — PRformer: MSE 0.162
2024-10-21 — LTBoost (drop_last=false): MSE 0.156
2024-12-23 — xPatch: MSE 0.153
Rank
Model
MSE
MAE
Paper
Code
Year
1
xPatch
0.153
0.240
xPatch: Dual-Stream Time Series Forecasting with Exponential Seasonal-Trend Decomposition
stitsyuk/xpatch
2024
2
LTBoost (drop_last=false)
0.156
0.243
LTBoost: Boosted Hybrids of Ensemble Linear and Gradient Algorithms for the Long-term Time Series Forecasting
hubtru/LTBoost
2024
3
PRformer
0.162
–
PRformer: Pyramidal Recurrent Transformer for Multivariate Time Series Forecasting
usualheart/prformer
2024
3
DiPE-Linear
0.162
–
Disentangled Interpretable Representation for Efficient Long-term Time Series Forecasting
wintertee/dipe-linear
2024
5
SCNN
0.163
–
Disentangling Structured Components: Towards Adaptive, Interpretable and Scalable Time Series Forecasting
JLDeng/SCNN
2023
6
RLinear
0.164
0.253
Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping
plumprc/rtsf
2023
6
TSMixer
0.164
0.255
TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting
ibm/tsfm
2023
8
MoLE-DLinear
0.168
–
Mixture-of-Linear-Experts for Long-term Time Series Forecasting
rogerni/mole
2023
9
TEFN
0.181
0.264
Time Evidence Fusion Network: Multi-source View in Long-Term Time Series Forecasting
WenjieDu/PyPOTS
·
ztxtech/Time-Evidence-Fusion-Network
2024
10
xPatch
0.153
0.240
xPatch: Dual-Stream Time Series Forecasting with Exponential Seasonal-Trend Decomposition
stitsyuk/xpatch
2024
11
LTBoost (drop_last=false)
0.156
0.243
LTBoost: Boosted Hybrids of Ensemble Linear and Gradient Algorithms for the Long-term Time Series Forecasting
hubtru/LTBoost
2024
12
PRformer
0.162
–
PRformer: Pyramidal Recurrent Transformer for Multivariate Time Series Forecasting
usualheart/prformer
2024
12
DiPE-Linear
0.162
–
Disentangled Interpretable Representation for Efficient Long-term Time Series Forecasting
wintertee/dipe-linear
2024
14
SCNN
0.163
–
Disentangling Structured Components: Towards Adaptive, Interpretable and Scalable Time Series Forecasting
JLDeng/SCNN
2023
15
RLinear
0.164
0.253
Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping
plumprc/rtsf
2023
15
TSMixer
0.164
0.255
TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting
ibm/tsfm
2023
17
MoLE-DLinear
0.168
–
Mixture-of-Linear-Experts for Long-term Time Series Forecasting
rogerni/mole
2023
18
TEFN
0.181
0.264
Time Evidence Fusion Network: Multi-source View in Long-Term Time Series Forecasting
WenjieDu/PyPOTS
·
ztxtech/Time-Evidence-Fusion-Network
2024
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