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[timeseries] Preprocess real-valued features for neural network models #4042

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merged 5 commits into from
Apr 5, 2024

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shchur
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@shchur shchur commented Apr 5, 2024

Description of changes:

  • Preprocess real-valued columns in known, past & static covariates for GluonTS models. We use the same logic as used by TORCH_NN model in AG-Tabular:
    • Boolean features are kept as-is
    • Skewed features (skewness > 0.99) are transformed with QuantileTransform
    • Remaining features are transformed with StandardScaler

To do:

  • Add tests

By submitting this pull request, I confirm that you can use, modify, copy, and redistribute this contribution, under the terms of your choice.

@shchur shchur requested a review from canerturkmen April 5, 2024 13:42
@shchur shchur mentioned this pull request Apr 5, 2024
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@yinweisu
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yinweisu commented Apr 5, 2024

Previous CI Run Current CI Run

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LGTM! Thanks!

@yinweisu
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yinweisu commented Apr 5, 2024

Previous CI Run Current CI Run

@yinweisu
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yinweisu commented Apr 5, 2024

Previous CI Run Current CI Run
fonttools==4.50.0 fonttools==4.51.0
fonttools==4.50.0 fonttools==4.51.0

@shchur shchur merged commit 5eca065 into autogluon:master Apr 5, 2024
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github-actions bot commented Apr 5, 2024

Job PR-4042-acffe07 is done.
Docs are uploaded to http://autogluon-staging.s3-website-us-west-2.amazonaws.com/PR-4042/acffe07/index.html

@shchur shchur deleted the normalize-feat-ts branch April 6, 2024 06:25
LennartPurucker pushed a commit to LennartPurucker/autogluon that referenced this pull request Jun 1, 2024
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3 participants