PriceForecast/shiyoujiaolvyongdataset/model_evaluation.csv

1	模型(Model)	平均平方误差(MSE)	均方根误差(RMSE)	平均绝对误差(MAE)
2	PatchTST	847.898	29.119	21.041
3	NLinear	1036.997	32.202	24.318
4	NHITS	1224.82	34.997	25.062
5	MLP	1687.576	41.08	29.488
6	TFT	2289.522	47.849	33.59
7	BiTCN	3020.992	54.964	40.577
8	Informer	3532.014	59.431	46.436
9	TiDE	3700.651	60.833	44.453
10	FEDformer	4694.675	68.518	52.676
11	TSMixer	5285.01	72.698	55.318
12	MLPMultivariate	5635.67	75.071	57.694
13	TSMixerx	6758.13	82.208	62.804
14	DeepNPTS	7644.172	87.431	70.142
15	DLinear	8446.178	91.903	73.653
16	GRU	11533.363	107.393	95.255
17	LSTM	11540.298	107.426	92.262
18	StemGNN	14027.959	118.44	89.743
19	iTransformer	15670.617	125.182	100.969
20	TCN	19821.416	140.789	118.182
21	DilatedRNN	21523.955	146.71	126.693
22	RNN	109475.398	330.871	278.113