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Multi-view support vector ordinal regression with data uncertainty.
- Source :
-
Information Sciences . Apr2022, Vol. 589, p516-530. 15p. - Publication Year :
- 2022
-
Abstract
- Ordinal regression (OR) is a paradigm which learns a prediction model on the data with ordered classes. Despite much progress in OR, the existing OR works learn the classifier from only one view and the multi-view learning in OR has not been considered. What is more, there may exist uncertain information in the multi-view OR data. In this paper, we put forward a novel approach, called multi-view support vector ordinal regression with uncertain data (MORU), which can improve the OR classifier by incorporating the multi-view information and handling the data uncertainty. In our method, a series of parallel hyperplanes are applied to separate the multi-view ordered data, and the uncertain information is considered in the input data. Then, we adopt a heuristic framework to solve the OR learning problem. Experimental results have illustrated that our method obtains superior performance to the existing OR techniques. [ABSTRACT FROM AUTHOR]
- Subjects :
- *HYPERPLANES
*PREDICTION models
*PROBLEM solving
Subjects
Details
- Language :
- English
- ISSN :
- 00200255
- Volume :
- 589
- Database :
- Academic Search Index
- Journal :
- Information Sciences
- Publication Type :
- Periodical
- Accession number :
- 155090899
- Full Text :
- https://doi.org/10.1016/j.ins.2021.12.128