Determining the accuracy in image supervised classification problems
Daniel Gomez, Javier Montero
Available Online August 2011.
- https://doi.org/10.2991/eusflat.2011.103How to use a DOI?
- Fuzzy image classification, Accuracy measures; Kappa Index.
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Daniel Gomez AU - Javier Montero PY - 2011/08 DA - 2011/08 TI - Determining the accuracy in image supervised classification problems BT - Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology PB - Atlantis Press SP - 342 EP - 349 SN - 1951-6851 UR - https://doi.org/10.2991/eusflat.2011.103 DO - https://doi.org/10.2991/eusflat.2011.103 ID - Gomez2011/08 ER -