The key theorem of statistical learning theory on possibility spaces

Author

Bai, Yun-Chao ; Ha, Ming-Hu

Author_Institution

Coll. of Econ., Hebei Univ., Baoding, China

Volume

7

fYear

2005

fDate

18-21 Aug. 2005

Firstpage

4374

Abstract

In this paper, we will further discuss the property of the credibility measure and give Tchebycheff´s inequality and a large number theorem. On possibility measure spaces, we will give some new concepts of the empirical risk functional, the expected risk functional and the empirical risk minimization inductive principle (ERM) according to the classical statistical learning theory. At last, we will give and prove the key theorem of the statistical learning on possibility measure spaces.

Keywords

learning (artificial intelligence); minimisation; minimum principle; possibility theory; risk analysis; statistical analysis; Tchebycheff inequality; credibility measure; possibility measure space; risk functional; risk minimization inductive principle; statistical learning theory; Additives; Chromium; Educational institutions; Extraterrestrial measurements; Machine learning; National electric code; Power measurement; Probability; Risk management; Statistical learning; Credibility measure; the empirical risk functional; the empirical risk minimization of principle; the expected risk functional; the key theorem;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on

Conference_Location

Guangzhou, China

Print_ISBN

0-7803-9091-1

Type

conf

DOI

10.1109/ICMLC.2005.1527708

Filename

1527708