Fuzzy-Rough Set Bireducts for Data Reduction
- Submitting institution
-
Aberystwyth University / Prifysgol Aberystwyth
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 30046415
- Type
- D - Journal article
- DOI
-
10.1109/TFUZZ.2019.2921935
- Title of journal
- IEEE Transactions on Fuzzy Systems
- Article number
- -
- First page
- 1840
- Volume
- 28
- Issue
- 8
- ISSN
- 1063-6706
- Open access status
- Compliant
- Month of publication
- June
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
-
- Citation count
- 1
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- First paper to propose the simultaneous reduction of both features and instances in data using fuzzy-rough set theory. Preliminary version (not submitted for REF) led to tutorial on fuzzy-rough data mining at FUZZ-IEEE 2019, the top conference in the area. Published in IEEE TFS, best journal in the subject area.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -