RT Artículo
T1 Restricted set classification: Who is there?
A1 Kuncheva, Ludmila I. .
A1 Rodríguez Diez, Juan José
A1 Jackson, Aaron S. .
K1 Pattern recognition
K1 Object classification
K1 Restricted set classification
K1 Compound decision problem
K1 Chess pieces classification
AB 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).
PB Elsevier
SN 0031-3203
YR 2017
FD 2017-03
LK http://hdl.handle.net/10259/4351
UL http://hdl.handle.net/10259/4351
LA eng
NO Spanish Ministry ofEconomy and Competitiveness through project TIN 2015-67534-P
DS Repositorio Institucional de la Universidad de Burgos
RD 25-feb-2020