The PIC-TDD Framework of Test Data Design for Pattern Recognition Systems

Xiangdong Wang, Ying Yang, Hong Liu and Yueliang Qian
Additional contact information
Xiangdong Wang: Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
Ying Yang: College of Information and Electrical Engineering, China Agricultural University, Beijing, China
Hong Liu: Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
Yueliang Qian: Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China

International Journal of Advanced Pervasive and Ubiquitous Computing (IJAPUC), 2014, vol. 6, issue 4, 43-62

Abstract: In this paper, a new approach is proposed for the design of test data for pattern recognition systems. In the theoretical framework put forward, performance on the population of data is viewed as expectation of a random variable, and the purpose of test is to estimate the parameter. While the most popular method of test data design is random sampling, a novel approach based on performance influencing classes is proposed, which can achieve unbiased estimation and the variance of estimation is much lower than that from random sample. The method is applied to the evaluation of systems for broadcasting news segmentation, and experimental results show the advantages over the random sampling approach.

Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 18/ijapuc.2014100104 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:japuc0:v:6:y:2014:i:4:p:43-62

Access Statistics for this article

International Journal of Advanced Pervasive and Ubiquitous Computing (IJAPUC) is currently edited by Tao Gao

More articles in International Journal of Advanced Pervasive and Ubiquitous Computing (IJAPUC) from IGI Global
Bibliographic data for series maintained by Journal Editor ().