An empirical study of testing independencies in Bayesian networks using rp-separation

作者：Butz Cory J^*; dos Santos Andre E; Oliveira Jhonatan S; Gonzales Christophe

来源：International Journal of Approximate Reasoning, 2018, 92: 270-278.

DOI：10.1016/j.ijar.2017.10.026

• Bayesian networks
• d-Separation
• Conditional independence

Directed separation (d-separation) played a fundamental role in the founding of Bayesian networks (BNs) and continues to be useful today in a wide range of applications. Given an independence to be tested, current implementations of d-separation explore the active part of a BN. On the other hand, an overlooked property of d-separation implies that d-separation need only consider the relevant part of a BN. We propose a new method for testing independencies in BNs, called relevant path separation (rp-separation), which explores the intersection between the active and relevant parts of a BN. Favourable experimental results are reported.

• 出版日期2018-1