Relaxing the local independence assumption for quantitative learning in acyclic directed graphical models through hierarchical partition models
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چکیده
The simplest method proposed by Spiegelhalter and Lauritzen (1990) to perform quantitative learning in ADG presents a potential weakness: the local independence assumption. We propose to alleviate this problem through the use of Hierarchical Partition Models. Our approach is compared with the previous one from an interpretative and predictive point of view.
منابع مشابه
Relaxing the Local Independence Assumption for QuantitativeLearning in Acyclic Directed Graphical Models through HierarchicalPartition
The simplest method proposed by Spiegelhal-ter and Lauritzen (1990) to perform quantitative learning in ADG presents a potential weakness: the local independence assumption. We propose to alleviate this problem through the use of Hierarchical Partition Models. Our approach is compared with the previous one from an interpretative and pre-dictive point of view.
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تاریخ انتشار 1999