Recovering the number of clusters in data sets with noise features using feature rescaling factors
- Submitting institution
-
University of Hertfordshire
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 22813410
- Type
- D - Journal article
- DOI
-
10.1016/j.ins.2015.06.039
- Title of journal
- Information Sciences
- Article number
- -
- First page
- 126
- Volume
- 324
- 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
-
-
- 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
-
1
- Research group(s)
-
-
- Citation count
- 132
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The feature-rescaling methods introduced in this paper have been applied by many researchers in a wide variety of fields, e.g. Aerospace, Genome Research, Neuroscience, Hydrology, Computer Science and machine learning/AI. A considerable number of studies that have used it have attracted a high number of citations themselves: 26 of the citing papers have attracted 10 or more citations and they have been published in journals like Genome Research, IEEE Transactions on Industrial Informatics, IEEE Sensors, Journal of Chemical Theory and Computation, Aerospace Science and Technology, J. Hydrology, NeuroImage, and Pattern Recognition, among others.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
