Random Balance: Ensembles of variable priors classifiers for imbalanced data
- Submitting institution
-
Bangor University / Prifysgol Bangor
- Unit of assessment
- 12 - Engineering
- Output identifier
- UoA12_37
- Type
- D - Journal article
- DOI
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10.1016/j.knosys.2015.04.022
- Title of journal
- Knowledge-Based Systems
- Article number
- -
- First page
- 96-111
- Volume
- 85
- Issue
- -
- ISSN
- 0950-7051
- Open access status
- Out of scope for open access requirements
- Month of publication
- May
- Year of publication
- 2015
- 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
-
3
- Research group(s)
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-
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The Random Balance ensemble method is one of the most successful methods for classification of imbalanced data to date and was a the core theme of a research project funded by the Ministry of Economy and Business of Spain, which led to five research visits by members of the team from the University of Burgos to Bangor and two further journal publications.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
