CONSTRUCTION OF BAYESIAN NETWORK STRUCTURES FROM DATA - A BRIEF SURVEY AND AN EFFICIENT ALGORITHM

被引：181

作者：

SINGH, M ^{[1
]}

VALTORTA, M ^{[1
]}

机构：

[1] UNIV S CAROLINA,DEPT COMP SCI,COLUMBIA,SC 29208

来源：

INTERNATIONAL JOURNAL OF APPROXIMATE REASONING | 1995年 / 12卷 / 02期

关键词：

BAYESIAN NETWORKS; PROBABILISTIC NETWORKS; PROBABILISTIC MODEL CONSTRUCTION; CONDITIONAL INDEPENDENCE;

D O I：

10.1016/0888-613X(94)00016-V

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 [模式识别与智能系统]; 0812 [计算机科学与技术]; 0835 [软件工程]; 1405 [智能科学与技术];

摘要：

Previous algorithms for the recovery of Bayesian belief network structures from data have been either highly dependent on conditional independence (CI) tests, or have required on ordering on the nodes to be supplied by the user. We present an algorithm that integrates these two approaches: CI tests are used to generate an ordering on the nodes from the database, which is then used to recover the underlying Bayesian network structure using a non-CI-test-based method. Results of the evaluation of the algorithm on a number of databases (e.g., ALARM, LED, and SOYBEAN) are presented. We also discuss some algorithm performance issues and open problems.

引用

页码：111 / 131

页数：21

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