Representing canonical models as probability trees

被引：0
|
作者：
del Sagrado, J [1 ]
Salmerón, A
机构：
[1] Univ Almeria, Dept Languages & Comp, Almeria 04120, Spain
[2] Univ Almeria, Dept Appl Math & Stat, Almeria 04120, Spain
来源：
CURRENT TOPICS IN ARTIFICIAL INTELLIGENCE | 2004年 / 3040卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Canonical models are useful because they simplify the construction of probabilistic models exploiting causal patterns. In this paper we study the relationships between canonical models and their representation and computation using probability trees, placing special emphasis on the approximation of very large canonical models.
引用
收藏
页码：478 / 487
页数：10
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