RT Book, Section
T1 Determining the accuracy in image supervised classification problems
A1 Gómez González, Daniel
A1 Montero De Juan, Francisco Javier
AB A large number of accuracy measures for crisp supervised classification have been developed in supervised image classification literature. Overall accuracy, Kappa index, Kappa location, Kappa histo and user accuracy are some well-known examples. In this work, we will extend and analyze some of these measures in a fuzzy framework to be able to measure the goodness of a given classifier in a supervised fuzzy classification system with fuzzy reference data. In addition with this, the measures here defined also take into account the preferences of the decision maker in order to differentiate some errors that must not be considered equal in the classification process.
PB Atlantis Press
YR 2011
FD 2011
LK https://hdl.handle.net/20.500.14352/45543
UL https://hdl.handle.net/20.500.14352/45543
LA eng
NO Gomez, D., Montero, J.: Determining the accuracy in image supervised classification problems. En: Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-2011). Atlantis Press, France (2011)
DS Docta Complutense
RD 9 abr 2025