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[FEAT] Add historical exogenous #453

Merged
merged 9 commits into from
Aug 30, 2024
Merged

[FEAT] Add historical exogenous #453

merged 9 commits into from
Aug 30, 2024

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elephaint
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@elephaint elephaint commented Aug 22, 2024 •
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  • Adds possibility to use historical exogenous variables. Basically, historical exogenous variables are those variables in df that are not in X_df
  • Updates docs to show how historical exogenous variable can be used

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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 213.936 199.132 2571.33 10604.2
total_time 2.7883 3.2169 0.0069 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 1.5392 2.8155 0.0046 0.0041

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 2.5769 5.2929 0.0055 0.0051

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 3.146 2.5787 0.0057 0.0053

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 2.5724 2.5366 0.0062 0.0055

Plot:

@elephaint elephaint requested a review from cchallu August 22, 2024 15:44
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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 2.7264 2.9095 0.0066 0.0041

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 4040.21 4110.79 5928.17 18859.2
total_time 2.3118 3.439 0.0043 0.0039

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 2.4519 2.3809 0.0053 0.0049

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 1.9898 1.3816 0.0055 0.0051

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 1.3607 1.4734 0.0056 0.0051

Plot:

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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 213.936 199.132 2571.33 10604.2
total_time 1.2466 2.4516 0.0062 0.0039

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 4040.21 4110.79 5928.17 18859.2
total_time 0.5904 0.6259 0.0044 0.0041

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 1.0521 2.5522 0.0058 0.0049

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 0.8045 1.5007 0.0054 0.0049

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 0.7117 0.6067 0.0057 0.0052

Plot:

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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 213.936 199.132 2571.33 10604.2
total_time 2.5275 1.4863 0.0068 0.004

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 4040.21 4110.79 5928.17 18859.2
total_time 0.7498 0.5507 0.0044 0.004

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 0.9982 1.3827 0.0057 0.0049

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 0.7031 0.7128 0.0059 0.0052

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 0.756 0.6132 0.0056 0.0053

Plot:

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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 213.936 199.132 2571.33 10604.2
total_time 1.3998 1.5525 0.0068 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 4040.21 4110.79 5928.17 18859.2
total_time 3.3667 0.9059 0.0046 0.0042

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 1.348 1.8516 0.0056 0.0053

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 1.1389 3.2896 0.0064 0.0058

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 2.3692 1.783 0.0058 0.0055

Plot:

@elephaint elephaint linked an issue Aug 28, 2024 that may be closed by this pull request
Exogenous Variables for Forecasting #380
Closed
@elephaint elephaint mentioned this pull request Aug 28, 2024
Closed
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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 213.936 199.132 2571.33 10604.2
total_time 1.9728 2.2696 0.0073 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 4040.21 4110.79 5928.17 18859.2
total_time 1.42 1.7078 0.0045 0.0041

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 1.6179 2.0037 0.0055 0.0053

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 1.684 1.3056 0.006 0.0053

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 1.6133 1.7474 0.0059 0.0055

Plot:

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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 213.936 199.132 2571.33 10604.2
total_time 1.8031 1.2482 0.0071 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 4040.21 4110.79 5928.17 18859.2
total_time 1.4338 2.5199 0.0046 0.0042

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 1.321 1.6929 0.0057 0.0052

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 1.2754 1.3702 0.0057 0.0051

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 1.726 1.7388 0.006 0.0053

Plot:

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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 6.8808 1.9429 0.0073 0.0042

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 1.1586 1.4599 0.0047 0.0042

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 2.2854 2.3682 0.0055 0.0051

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 1.3421 1.294 0.0058 0.0052

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 1.477 1.3985 0.0057 0.0051

Plot:

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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 2.9225 3.5362 0.0068 0.0042

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 1.2794 1.3646 0.0045 0.0041

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 2.5152 2.8837 0.0054 0.0049

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 1.6199 11.958 0.0055 0.005

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 6.5496 1.4689 0.0056 0.0051

Plot:

jmoralez
jmoralez approved these changes Aug 29, 2024
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LGTM on the implementation. Maybe @mergenthaler has some SEO tricks up his sleeve.

@elephaint elephaint merged commit f44938a into main Aug 30, 2024
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@elephaint elephaint deleted the feature/hist_exog branch August 30, 2024 18:06
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@jmoralez jmoralez jmoralez approved these changes

@cchallu cchallu Awaiting requested review from cchallu

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Exogenous Variables for Forecasting
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@elephaint @jmoralez