Automated Feature Engineering Using Meta-Learning for Efficient and Generalizable Data Science Pipelines
Feature engineering remains one of the most time-intensive and expertise-dependent stages in machine learning pipelines, often limiting scalability and reproducibility. Despite advances in automated machine learning, existing systems largely emphasize model and hyperparameter optimization while leav...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | en en |
| Published: |
INTI International University
2026
|
| Subjects: | |
| Online Access: | http://eprints.intimal.edu.my/2301/1/jods2026_04.pdf http://eprints.intimal.edu.my/2301/2/854 http://eprints.intimal.edu.my/2301/ http://ipublishing.intimal.edu.my/jods.html |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|