Latent Variable Study Algorithm Based on Grey Cluster Relation Analysis Method

机译：基于灰色聚类关系分析法的潜变量研究算法

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摘要

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.

机译：提出了一种基于灰色聚类关联分析的潜在变量研究算法。灰色聚类方法对现有数据进行了初步的统计分析，从而建立了变量之间的关系，并建立了贝叶斯候选预模型。与现有的启发式方法相比，可以有效地减少模型前的搜索空间，减少EM算法的调用时间。简化了潜在结构的研究进展，使效率得到了一定程度的提高。

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来源
《2009年中国控制与决策会议（2009 Chinese Control and Decision Conference）论文集》|2009年|3604-3607|共4页
会议地点 Guilin(CN)
作者
QU Ying; JIA Jian; WU Qi-zong;
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作者单位

HeiBei University of Science and Technology Shijiazhuang 050018 China School of Management and Economics Beijing Institute of Technology Beijing 100081;

Hebei Far East Harris Communications Company LimitedShijiazhuang 050200 China;

School of Management and Economics Beijing Institute of Technology Beijing 100081;

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关键词
Grey Cluster; Latent Variable; Pre-Model; Bayesian Network;

机译：灰色集群；潜在变量；预模型贝叶斯网络;

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Latent Variable Study Algorithm Based on Grey Cluster Relation Analysis Method

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