Explaining support vector machines: A color based nomogram
- Submitting institution
-
Liverpool John Moores University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 964
- Type
- D - Journal article
- DOI
-
10.1371/journal.pone.0164568
- Title of journal
- PLoS One
- Article number
- e0164568
- First page
- e0164568
- Volume
- 11
- Issue
- 10
- ISSN
- 1932-6203
- Open access status
- Compliant
- Month of publication
- October
- Year of publication
- 2016
- 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
-
4
- Research group(s)
-
-
- Citation count
- 14
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper derives a graphical interface to communicate the SVM to non-expert users. The nomogram is commonly used for clinical decision support and it is acknowledged as a readily understood representation of linear models. Here, it is used for the first time to represent the operation of an algorithm widely regarded as black box. It relates to an invited talk at the prestigious Schloss Dagstuhl in 2016 and two Keynote Addresses, at 13th IEEE Latin American Summer School on Computational Intelligence, 2017 and 13th International Conference on Data Science and Knowledge Engineering for Sensing Decision Support, 2018.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
