Latent variable study algorithm based on grey cluster relation analysis method

Authors:
Ying Qu;Jian Jia;Qi-Zong Wu
Affiliations:
HeiBei University of Science and Technology, Shijiazhuang, China and School of Management and Economics, Beijing Institute of Technology, Beijing;Hebei Far East Harris Communications Company Limited, Shijiazhuang, China;School of Management and Economics, Beijing Institute of Technology, Beijing
Venue:
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Year:
2009

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Abstract

A latent variable study algorithm based on grey cluster relation analysis method was proposed. Grey cluster method give a preliminary statistical analysis on existing data, thus the relationship among variables were established and candidate pre-models of Bayesian was built up. Compared with the existing heuristic methods, it coulds effectively reduce the pre-model search space, decrease the call times of EM Algorithm. The study progress of latent structure is simplified, so the efficiency of it was improved to some extent.