Gómez González, DanielMontero De Juan, Francisco Javier2023-06-202023-06-202011Gomez, 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)10.2991/eusflat.2011.103https://hdl.handle.net/20.500.14352/45543A 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.engbook parthttps//doi.org/10.2991/eusflat.2011.103http://www.atlantis-press.com/php/download_paper.php?id=2288open access519.8Fuzzy image classificationAccuracy measuresKappa IndexInvestigación operativa (Matemáticas)1207 Investigación Operativa