2026-04-17T07:29:06Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/43512022-04-29T12:02:45Zcom_10259_4219com_10259_5086com_10259_2604col_10259_4220
Repositorio Institucional de la Universidad de Burgos
author
Kuncheva, Ludmila I. .
author
RodrÃguez Diez, Juan José
author
Jackson, Aaron S. .
2017-03-08T12:31:36Z
2019-03-01T03:45:06Z
2017-03
0031-3203
http://hdl.handle.net/10259/4351
We consider a problem where a set X of N objects (instances) coming from c classes have to be classified simultaneously. A restriction is imposed on X in that the maximum possible number of objects from each class is known, hence we dubbed the problem who-is-there? We compare three approaches to this problem: (1) independent classification whereby each object is labelled in the class with the largest posterior probability; (2) a greedy approach which enforces the restriction; and (3) a theoretical approach which, in addition, maximises the likelihood of the label assignment, implemented through the Hungarian assignment algorithm. Our experimental study consists of two parts. The first part includes a custom-made chess data set where the pieces on the chess board must be recognised together from an image of the board. In the second part, we simulate the restricted set classification scenario using 96 datasets from a recently collated repository (University of Santiago de Compostela, USC). Our results show that the proposed approach (3) outperforms approaches (1) and (2).
eng
Attribution-NonCommercial-NoDerivatives 4.0 International
Pattern recognition
Object classification
Restricted set classification
Compound decision problem
Chess pieces classification
Restricted set classification: Who is there?
info:eu-repo/semantics/article
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URL
https://riubu.ubu.es/bitstream/10259/4351/1/Kuncheva-PR_2017.pdf
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https://riubu.ubu.es/bitstream/10259/4351/6/Kuncheva-PR_2017.pdf.txt
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Kuncheva-PR_2017.pdf.txt