کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
397894 | 1438455 | 2014 | 11 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Learning AMP chain graphs and some marginal models thereof under faithfulness Learning AMP chain graphs and some marginal models thereof under faithfulness](/preview/png/397894.png)
This paper deals with chain graphs under the Andersson–Madigan–Perlman (AMP) interpretation. In particular, we present a constraint based algorithm for learning an AMP chain graph a given probability distribution is faithful to. Moreover, we show that the extension of Meek's conjecture to AMP chain graphs does not hold, which compromises the development of efficient and correct score + search learning algorithms under assumptions weaker than faithfulness.We also study the problem of how to represent the result of marginalizing out some nodes in an AMP CG. We introduce a new family of graphical models that solves this problem partially. We name this new family maximal covariance–concentration graphs because it includes both covariance and concentration graphs as subfamilies.
Journal: International Journal of Approximate Reasoning - Volume 55, Issue 4, June 2014, Pages 1011–1021