Towards scalable fuzzy–rough feature selection
- Submitting institution
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Aberystwyth University / Prifysgol Aberystwyth
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 6724188
- Type
- D - Journal article
- DOI
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10.1016/j.ins.2015.06.025
- Title of journal
- Information Sciences
- Article number
- -
- First page
- 1
- Volume
- 323
- Issue
- -
- ISSN
- 0020-0255
- Open access status
- Out of scope for open access requirements
- Month of publication
- June
- Year of publication
- 2015
- URL
-
-
- Supplementary information
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-
- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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1
- Research group(s)
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-
- Citation count
- 27
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- First approach to make fuzzy-rough set methods applicable to much larger datasets. Led to further theoretical developments and the application of fuzzy-rough sets to big data (Lenz, Ghent University, Belgium; Riza, University of Granada, Spain; Zhang, Wuhan University of Technology, China), and a special issue "Fuzzy-rough sets for big data" in IEEE Trans. Fuzzy Systems, the premier journal in the field.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -