Contextualizing support vector machine predictions
- Author
- Marcelo Eduardo Loor Romero (UGent) and Guy De Tré (UGent)
- Organization
- Project
- Abstract
- Classification in artificial intelligence is usually understood as a process whereby several objects are evaluated to predict the class(es) those objects belong to. Aiming to improve the interpretability of predictions resulting from a support vector machine classification process, we explore the use of augmented appraisal degrees to put those predictions in context. A use case, in which the classes of handwritten digits are predicted, illustrates how the interpretability of such predictions is benefitted from their contextualization.
- Keywords
- Explainable artificial intelligence, Augmented appraisal degrees, Context handling, Support vector machine classification, BLACK-BOX
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-8677641
- MLA
- Loor Romero, Marcelo Eduardo, and Guy De Tré. “Contextualizing Support Vector Machine Predictions.” INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, vol. 13, no. 1, 2020, pp. 1483–97, doi:10.2991/ijcis.d.200910.002.
- APA
- Loor Romero, M. E., & De Tré, G. (2020). Contextualizing support vector machine predictions. INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, 13(1), 1483–1497. https://doi.org/10.2991/ijcis.d.200910.002
- Chicago author-date
- Loor Romero, Marcelo Eduardo, and Guy De Tré. 2020. “Contextualizing Support Vector Machine Predictions.” INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS 13 (1): 1483–97. https://doi.org/10.2991/ijcis.d.200910.002.
- Chicago author-date (all authors)
- Loor Romero, Marcelo Eduardo, and Guy De Tré. 2020. “Contextualizing Support Vector Machine Predictions.” INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS 13 (1): 1483–1497. doi:10.2991/ijcis.d.200910.002.
- Vancouver
- 1.Loor Romero ME, De Tré G. Contextualizing support vector machine predictions. INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS. 2020;13(1):1483–97.
- IEEE
- [1]M. E. Loor Romero and G. De Tré, “Contextualizing support vector machine predictions,” INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, vol. 13, no. 1, pp. 1483–1497, 2020.
@article{8677641,
abstract = {{Classification in artificial intelligence is usually understood as a process whereby several objects are evaluated to predict the class(es) those objects belong to. Aiming to improve the interpretability of predictions resulting from a support vector machine classification process, we explore the use of augmented appraisal degrees to put those predictions in context. A use case, in which the classes of handwritten digits are predicted, illustrates how the interpretability of such predictions is benefitted from their contextualization.}},
author = {{Loor Romero, Marcelo Eduardo and De Tré, Guy}},
issn = {{1875-6883}},
journal = {{INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS}},
keywords = {{Explainable artificial intelligence,Augmented appraisal degrees,Context handling,Support vector machine classification,BLACK-BOX}},
language = {{eng}},
number = {{1}},
pages = {{1483--1497}},
title = {{Contextualizing support vector machine predictions}},
url = {{http://doi.org/10.2991/ijcis.d.200910.002}},
volume = {{13}},
year = {{2020}},
}
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