Parallelization of the PC Algorithm
This paper describes a parallel version of the PC algorithm for learning the structure of a Bayesian network from data. The PC algorithm is a constraint-based algorithm consisting of fi ve steps where the first step is to perform a set of (conditional) independence tests while the remaining four...
Main Authors: | Madsen, Anders L., Jensen, Frank, Salmerón Cerdán, Antonio, Langseth, Helge, Nielsen, Thomas D. |
---|---|
Formato: | info:eu-repo/semantics/article |
Idioma: | English |
Publicado em: |
2017
|
Acesso em linha: | http://hdl.handle.net/10835/4856 |
Registos relacionados
-
Parallel Filter-Based Feature Selection Based on Balanced Incomplete Block Designs
Por: Salmerón Cerdán, Antonio, et al.
Publicado em: (2017) -
Parallel Importance Sampling in Conditional Linear Gaussian Networks
Por: Salmerón Cerdán, Antonio, et al.
Publicado em: (2017) -
A New Method for Vertical Parallelisation of TAN Learning Based on Balanced Incomplete Block Designs
Por: Madsen, Anders L., et al.
Publicado em: (2017) -
MPE inference in Conditional Linear Gaussian Networks
Por: Salmerón Cerdán, Antonio, et al.
Publicado em: (2017) - Fundamentals of parallel processing