Perez-Ortiz, M;
Fernandes, K;
Cruz, R;
Cardoso, JS;
Briceno, J;
Hervas-Martinez, C;
(2017)
Fine-to-Coarse Ranking in Ordinal and Imbalanced Domains: An Application to Liver Transplantation.
In: Rojas, I and Joya, G and Catala, A, (eds.)
Advances in Computational Intelligence (Proceedings Part 1).
(pp. pp. 525-537).
Springer: Cham, Switzerland.
Preview |
Text
2017MOrtizIWANN.pdf - Accepted Version Download (17MB) | Preview |
Abstract
Nowadays imbalanced learning represents one of the most vividly discussed challenges in machine learning. In these scenarios, one or some of the classes in the problem have a significantly lower a priori probability, usually leading to trivial or non-desirable classifiers. Because of this, imbalanced learning has been researched to a great extent by means of different approaches. Recently, the focus has switched from binary classification to other paradigms where imbalanced data also arise, such as ordinal classification. This paper tests the application of learning pairwise ranking with multiple granularity levels in an ordinal and imbalanced classification problem where the aim is to construct an accurate model for donor-recipient allocation in liver transplantation. Our experiments show that approaching the problem as ranking solves the imbalance issue and leads to a competitive performance.
| Type: | Proceedings paper |
|---|---|
| Title: | Fine-to-Coarse Ranking in Ordinal and Imbalanced Domains: An Application to Liver Transplantation |
| Event: | 14th International Work-Conference on Artificial Neural Networks (IWANN 2017), 14-16 June 2017, Cadiz, Spain |
| Location: | Cadiz, SPAIN |
| Dates: | 14 June 2017 - 16 June 2017 |
| ISBN-13: | 978-3-319-59146-9 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/978-3-319-59147-6 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Imbalanced data, Ranking Ordinal classification, Over-sampling |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10069043 |
Loading...
Loading...Loading...Loading...Archive Staff Only
 |
View Item |
