🌿 Fern Regeneration -- November 7, 2023

[fern-api]

This PR regenerates code to match the latest API Definition.

[github-actions]

Experiment 1: air-passengers

Description:

variable	experiment
h	12
season_length	12
freq	MS
level	None
n_windows	1

Results:

metric	TimeGPT	SeasonalNaive	Naive
mae	12.6793	47.8333	76
mape	0.027	0.0999	0.1425
mse	213.936	2571.33	10604.2
total_time	3.6369	7.7748	0.7049

Plot:

Experiment 2: air-passengers

Description:

variable	experiment
h	24
season_length	12
freq	MS
level	None
n_windows	1

Results:

metric	TimeGPT	SeasonalNaive	Naive
mae	58.1031	71.25	115.25
mape	0.1257	0.1552	0.2358
mse	4040.21	5928.17	18859.2
total_time	1.9508	0.0068	0.0064

Plot:

Experiment 3: electricity-multiple-series

Description:

variable	experiment
h	24
season_length	24
freq	H
level	None
n_windows	1

Results:

metric	TimeGPT	SeasonalNaive	Naive
mae	4.8617	5.6289	5.2381
mape	0.6816	0.7654	0.6328
mse	40.5749	63.023	50.8454
total_time	2.24	0.0151	0.0146

Plot:

Experiment 4: electricity-multiple-series

Description:

variable	experiment
h	168
season_length	24
freq	H
level	None
n_windows	1

Results:

metric	TimeGPT	SeasonalNaive	Naive
mae	8.3102	9.3176	12.6464
mape	1.382	1.0786	1.4208
mse	165.13	202.596	336.086
total_time	3.1847	0.0167	0.0164

Plot:

Experiment 5: electricity-multiple-series-with-ex-vars

Description:

variable	experiment
h	24
season_length	24
freq	H
level	None
n_windows	1

Results:

metric	TimeGPT	SeasonalNaive	Naive
mae	5.5206	5.6289	5.2381
mape	0.4674	0.7654	0.6328
mse	40.9623	63.023	50.8454
total_time	5.3155	0.8085	0.4715

Plot:

Experiment 6: electricity-multiple-series-with-ex-vars

Description:

variable	experiment
h	168
season_length	24
freq	H
level	None
n_windows	1

Results:

metric	TimeGPT	SeasonalNaive	Naive
mae	7.5605	9.3176	12.6464
mape	1.371	1.0786	1.4208
mse	135.78	202.596	336.086
total_time	4.4861	0.0204	0.0194

Plot:

[AzulGarza]

Problem persists. #151 should finally solve it.