PriceForecast/juxitingzhoududataset/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	642.386	25.345	17.595
3	TFT	688.789	26.245	18.33
4	MLP	816.516	28.575	20.349
5	NHITS	878.17	29.634	20.56
6	Informer	885.199	29.752	20.666
7	NLinear	903.16	30.053	20.318
8	TSMixerx	1112.102	33.348	23.435
9	BiTCN	1173.803	34.261	24.163
10	TiDE	1649.537	40.614	29.023
11	DeepNPTS	1869.962	43.243	32.379
12	TSMixer	2751.218	52.452	36.396
13	RNN	2847.392	53.361	44.101
14	DLinear	3353.619	57.91	43.041
15	MLPMultivariate	3576.635	59.805	36.229
16	StemGNN	3949.092	62.842	42.198
17	GRU	4915.715	70.112	59.132
18	iTransformer	7841.481	88.552	63.528
19	TCN	10411.853	102.038	91.581
20	LSTM	29510.061	171.785	154.489
21	DilatedRNN	300681.875	548.345	522.002