Title :
Bayes classifier and loss functions
Author :
E. Ocelíková;D. Klimešová
Author_Institution :
Technical University of Koš
Abstract :
This paper deals with the classification of objects into the limited number of classes. The objects are characterized by n-features. The paper focuses on the Bayes classifier based on the probability principle with the fixed number of the features during the classification process. The Bayes classifier which uses criterion of the minimum error was applied on the set of the multispectral data. They represent real images of the Earth surface obtained from remote Earth sensing. The paper describes experience and results obtained during the classification of extensive set of these multispectral data with the Bayes classifier using the symmetric and diagonal loss function.
Keywords :
"Presses","Earth","Informatics","Electrical engineering","Sensors","Covariance matrix","Cost accounting"
Conference_Titel :
Applied Machine Intelligence and Informatics (SAMI), 2011 IEEE 9th International Symposium on
Print_ISBN :
978-1-4244-7429-5
DOI :
10.1109/SAMI.2011.5738907