Title :
Exact classification error in bayes classifier with fuzzy observations
Author_Institution :
Dept. of Syst. & Comput. Networks, Wroclaw Univ. of Technol., Wroclaw, Poland
Abstract :
The paper considers the problem of classification error in pattern recognition. This model of classification is primarily based on the Bayes rule and secondarily on the notion of fuzzy numbers. A probability of misclassifications is derived for a classifier under the assumption that the features are class-conditionally statistically independent, and we have fuzzy information on object features instead of exact information. Numerical example of this difference concludes the work.
Keywords :
Bayes methods; fuzzy set theory; pattern classification; probability; Bayes classifier; classification error; fuzzy observation; pattern recognition; Approximation error; Bayesian methods; Fuzzy sets; Pattern analysis; Pattern recognition; Uncertainty; Bayes decision rule; fuzzy observations; probability of error;
Conference_Titel :
Information and Automation for Sustainability (ICIAFs), 2010 5th International Conference on
Conference_Location :
Colombo
Print_ISBN :
978-1-4244-8549-9
DOI :
10.1109/ICIAFS.2010.5715672
