Markov Library: A Tool for Computing Ideals Associated to Bayesian Networks
نویسندگان
چکیده
The Markov library contains methods to compute the ideals and primary decomposition associated to Bayesian networks described in [1]. This library is implemented in a computer algebra system, Singular ([2]). This document describes how to use this library for the various computations. In Section 1, we show how to compute various ideals associated to Bayesian networks without hidden variables. In Section 2, we describe how to compute the polynomial constraints for Bayesian networks with hidden variables.
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