DISCOVERING CAUSAL RELATIONS FROM CROSS-SECTIONAL DATA

被引：0

作者：

Yang, Jing ^{[1
]}

Wang, Aiguo ^{[1
]}

Wang, Kunxia ^{[1
]}

Li, Lian ^{[1
]}

Pan, Xiang

机构：

[1] Hefei Univ Technol, Sch Comp & Informat, Anhui Prov Key Lab Affect Comp & Adv Intelligent, Hefei, Peoples R China

来源：

4TH INTERNATIONAL CONFERENCE ON SOFTWARE TECHNOLOGY AND ENGINEERING (ICSTE 2012) | 2012年

关键词：

Cross-sectional data; Bayesian network; Causal relations;

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

This study is to verify that the Bayesian Network can be used for discovering causal relations from cross-sectional data. Using the PCB, LIMB, and TC algorithm, this study analyzes causal relations in the real data from the National Health and Nutrition Examination Survey. Experimental results show that these algorithms can discover causal relations to various degrees.

引用

页码：63 / 67

页数：5

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