Polytomous ordering theory algorithm based on empirical distribution critical value

Hsiang Chuan Liu, Shih Neng Wu, Hsien Chang Tsai, Yih Chang Ou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Liu's polytomous ordering theory algorithm can be used for any testing with homogeneous or heterogeneous polytomous response. It is more useful than other well known polytomous ordering theory. However, its threshold limit value is a fixed value, lacking of statistical meaning, In this paper, the authors provide an improved threshold limit value by using the empirical distribution critical value of all the values of the ordering indices between any two items. For comparing the performance of two ordering theory models, a calculus test with polytomous items of Chung Chou Institute of Technology is conducted. The experimental results show that the new method has the better performance. A computer program is developed for the proposed method.

Original languageEnglish
Title of host publicationProceedings of 2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011
Pages1101-1106
Number of pages6
DOIs
Publication statusPublished - 2011 Nov 7
Event2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011 - Guilin, Guangxi, China
Duration: 2011 Jul 102011 Jul 13

Publication series

NameProceedings - International Conference on Machine Learning and Cybernetics
Volume3
ISSN (Print)2160-133X
ISSN (Electronic)2160-1348

Other

Other2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011
CountryChina
CityGuilin, Guangxi
Period11-07-1011-07-13

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All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Human-Computer Interaction

Cite this

Liu, H. C., Wu, S. N., Tsai, H. C., & Ou, Y. C. (2011). Polytomous ordering theory algorithm based on empirical distribution critical value. In Proceedings of 2011 International Conference on Machine Learning and Cybernetics, ICMLC 2011 (pp. 1101-1106). [6016891] (Proceedings - International Conference on Machine Learning and Cybernetics; Vol. 3). https://doi.org/10.1109/ICMLC.2011.6016891