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AutoSmart
Introduced by Zhipeng Luo et al. in AutoSmart: An Efficient and Automatic Machine Learning framework for Temporal Relational Data
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
AutoSmart is AutoML framework for temporal relational data. The framework includes automatic data processing, table merging, feature engineering, and model tuning, integrated with a time&memory control unit.
Papers archive 2025-07-28
1 shown of 1, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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AutoSmart: An Efficient and Automatic Machine Learning framework for Temporal Relational Data 9 Sep 2021 · 1 repository · arXiv:2109.04115
Tasks archive 2025-07-28
3 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
| Task | Papers |
|---|---|
| AutoML | 1 |
| BIG-bench Machine Learning | 1 |
| Feature Engineering | 1 |
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections