Update openapi json file

[AzulGarza]

Created by Github action

[github-actions[bot]]

Experiment Results

Experiment 1: air-passengers

Description:

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

Results:

metric	timegpt-1	timegpt-1-long-horizon	SeasonalNaive	Naive
mae	12.6793	11.0623	47.8333	76
mape	0.027	0.0232	0.0999	0.1425
mse	213.935	199.132	2571.33	10604.2
total_time	1.7582	2.9304	0.0081	0.0043

Plot:

Experiment 2: air-passengers

Description:

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

Results:

metric	timegpt-1	timegpt-1-long-horizon	SeasonalNaive	Naive
mae	58.1031	58.4587	71.25	115.25
mape	0.1257	0.1267	0.1552	0.2358
mse	4040.22	4110.79	5928.17	18859.2
total_time	1.6573	3.3546	0.0051	0.0044

Plot:

Experiment 3: electricity-multiple-series

Description:

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

Results:

metric	timegpt-1	timegpt-1-long-horizon	SeasonalNaive	Naive
mae	178.293	268.121	269.23	1331.02
mape	0.0234	0.0311	0.0304	0.1692
mse	121588	219457	213677	4.68961e+06
total_time	1.5617	3.3249	0.0074	0.0063

Plot:

Experiment 4: electricity-multiple-series

Description:

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

Results:

metric	timegpt-1	timegpt-1-long-horizon	SeasonalNaive	Naive
mae	465.532	346.984	398.956	1119.26
mape	0.062	0.0437	0.0512	0.1583
mse	835121	403787	656723	3.17316e+06
total_time	3.7437	2.3555	0.0069	0.0063

Plot:

Experiment 5: electricity-multiple-series

Description:

variable	experiment
h	336
season_length	24
freq	H
level	None
n_windows	1

Results:

metric	timegpt-1	timegpt-1-long-horizon	SeasonalNaive	Naive
mae	558.649	459.769	602.926	1340.95
mape	0.0697	0.0566	0.0787	0.17
mse	1.22721e+06	739135	1.61572e+06	6.04619e+06
total_time	3.5539	4.4656	0.007	0.0064

Plot:

[github-actions[bot]]

Experiment Results

Experiment 1: air-passengers

Description:

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

Results:

metric	timegpt-1	timegpt-1-long-horizon	SeasonalNaive	Naive
mae	12.6793	11.0623	47.8333	76
mape	0.027	0.0232	0.0999	0.1425
mse	213.935	199.132	2571.33	10604.2
total_time	1.908	1.6488	0.0086	0.0045

Plot:

Experiment 2: air-passengers

Description:

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

Results:

metric	timegpt-1	timegpt-1-long-horizon	SeasonalNaive	Naive
mae	58.1031	58.4587	71.25	115.25
mape	0.1257	0.1267	0.1552	0.2358
mse	4040.22	4110.79	5928.17	18859.2
total_time	1.5895	1.6647	0.0055	0.0046

Plot:

Experiment 3: electricity-multiple-series

Description:

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

Results:

metric	timegpt-1	timegpt-1-long-horizon	SeasonalNaive	Naive
mae	178.293	268.121	269.23	1331.02
mape	0.0234	0.0311	0.0304	0.1692
mse	121588	219457	213677	4.68961e+06
total_time	1.6047	1.8579	0.0075	0.0069

Plot:

Experiment 4: electricity-multiple-series

Description:

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

Results:

metric	timegpt-1	timegpt-1-long-horizon	SeasonalNaive	Naive
mae	465.532	346.984	398.956	1119.26
mape	0.062	0.0437	0.0512	0.1583
mse	835120	403787	656723	3.17316e+06
total_time	5.6279	3.0553	0.0072	0.007

Plot:

Experiment 5: electricity-multiple-series

Description:

variable	experiment
h	336
season_length	24
freq	H
level	None
n_windows	1

Results:

metric	timegpt-1	timegpt-1-long-horizon	SeasonalNaive	Naive
mae	558.649	459.769	602.926	1340.95
mape	0.0697	0.0566	0.0787	0.17
mse	1.22721e+06	739135	1.61572e+06	6.04619e+06
total_time	5.2312	1.9492	0.0074	0.0068

Plot: