Feature selection for high dimensional imbalanced class data using harmony search
- Submitting institution
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Aberystwyth University / Prifysgol Aberystwyth
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11008880
- Type
- D - Journal article
- DOI
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10.1016/j.engappai.2016.10.008
- Title of journal
- Engineering Applications of Artificial Intelligence
- Article number
- -
- First page
- 38
- Volume
- 57
- Issue
- -
- ISSN
- 0952-1976
- Open access status
- Compliant
- Month of publication
- October
- Year of publication
- 2016
- 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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4
- Research group(s)
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-
- Citation count
- 59
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Novel approach for feature selection in high-dimensional imbalanced class data, having led to a range of successful applications globally, most notably, for expertise estimation in crowdsourcing (Moayedikia, 2019) and biomedical data analysis (Sharifai and Zainol, 2019). It has also motivated many further developments by researchers, e.g.: University of Jordan (Faris et al., 2018), Jadavpur University, India (Ghosh et al., 2019), University of Girona, Spain (Khawaldeh et al., 2017), China University of Mining and Technology (Xu et al., 2017), Universidad de Guadalajara (Fausto et al., 2019), Tomsk State University, Russia (Hodashinsky et al., 2019), and Canadian University Dubai (Kamalov, 2019).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -