July 2021
Intermediate to advanced
274 pages
6h 50m
English
Content preview from Bayesian Networks, 2nd Edition
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7
Software for Bayesian Networks
The difficulty of implementing versatile software for general classes of graphical models and the varying focus in different disciplines limit the applications of BNs compared to the state of the art in the literature. Nevertheless, the number of R packages for BNs has been slowly increasing in recent years. In this chapter we will provide an overview of available software packages, without pretending to be exhaustive, and we will introduce some classic R packages dealing with different aspects of BN learning and inference.
7.1 An Overview of R Packages
There are several packages on CRAN dealing with BNs. They can be divided in two categories: those that implement structure and parameter learning and those ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.