Interpretable Automated Feature Engineering: A Comprehensive Review with a Focus on Dynamic and Stationary Environments
This paper presents a comprehensive review of Automated Feature Engineering (AFE) methods, with a focus on their application in static data environments and explores recent advancements in dynamic Feature Engineering (FE) for evolving data contexts. A
Authors
- Katarzyna Musial-Gabrys
- Thanh Tung Khuat (ORCID: https://orcid.org/0000-0002-6456-8530)
- Dilshan Sonnadara (ORCID: https://orcid.org/0009-0003-7845-8855)
- Bogdan Gabryś (ORCID: https://orcid.org/0000-0002-0790-2846)
Institutions
- University of Technology Sydney (AU)
Publication Details
- Published
- 2025-10-14
- DOI
- https://doi.org/10.36227/techrxiv.176045781.15553175/v1
- Primary Topic
- Machine Learning and Data Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- University of Technology Sydney
- RMIT University