Title :
Quasi-pseudo-metric of measurable classifiers
Author :
Chen, Shao-Bai ; Tian, Sen-ping ; Mao, Zong-yuan
Author_Institution :
Coll. of Autom. & Eng., South China Univ. of Technol., Guangzhou, China
Abstract :
This paper is concerned with the quasi-pseudo-metrics of measurable classifiers in pattern recognition problems. A quasi-pseudo-metric of measurable classifiers in probability spaces is proposed, which is an average expense between classifiers. The optimal classifiers in subspace and their estimations are investigated and two important examples are discussed in the quasi-pseudo-metric space.
Keywords :
Bayes methods; pattern classification; probability; measurable classifier quasipseudometric; optimal classifier; pattern recognition; probability space; Application software; Automation; Computer applications; Computer errors; Educational institutions; Electronic mail; Extraterrestrial measurements; Loss measurement; Pattern recognition; Space technology; Pattern recognition; measurable classifier; quasi-pseudo-metric;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1527701
