Finding rough and fuzzy-rough set reducts with SAT
- Submitting institution
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Aberystwyth University / Prifysgol Aberystwyth
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 6724186
- Type
- D - Journal article
- DOI
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10.1016/j.ins.2013.07.033
- Title of journal
- Information Sciences
- Article number
- -
- First page
- 100
- Volume
- 255
- Issue
- -
- ISSN
- 0020-0255
- Open access status
- Out of scope for open access requirements
- Month of publication
- August
- Year of publication
- 2014
- URL
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- 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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2
- Research group(s)
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- Citation count
- 45
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- First approach to approximate feature selection with SAT. Led to many further developments regarding the use of discernibility matrices for fuzzy-rough sets (e.g., Dai et al., 2017; Shi et al., 2019; Liu et al., 2020) and fuzzy-rough feature selection in general (e.g., Eskandari and Javidi, 2016; Li et al., 2016; Wang et al., 2019; Chen et al., 2019; Zhao et al., 2019). Information Sciences is a leading journal in the area. Led to special session "Fuzzy and Rough Hybridisation" at the foremost bi-annual conference in computational intelligence, WCCI 2020.
- Author contribution statement
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- Non-English
- No
- English abstract
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