Learning Conditional Distributions using Mixtures of Truncated Basis Functions
Mixtures of Truncated Basis Functions (MoTBFs) have recently been proposed for modelling univariate and joint distributions in hybrid Bayesian networks. In this paper we analyse the problem of learning conditional MoTBF distributions from data. Our approach utilizes a new technique for learning...
Huvudupphovsmän: | Pérez-Bernabé, Inmaculada, Salmerón Cerdán, Antonio, Langseth, Helge |
---|---|
Materialtyp: | info:eu-repo/semantics/article |
Språk: | English |
Publicerad: |
2017
|
Länkar: | http://hdl.handle.net/10835/4859 |
Liknande verk
Liknande verk
-
Learning Mixtures of Truncated Basis Functions from Data
av: Langseth, Helge, et al.
Publicerad: (2017) -
Mixtures of Truncated Basis Functions
av: Langseth, Helge, et al.
Publicerad: (2017) -
MoTBFs: An R Package for Learning Hybrid Bayesian Networks Using Mixtures of Truncated Basis Functions
av: Maldonado González, Ana Devaki, et al.
Publicerad: (2023) -
Learning hybrid Bayesian networks using mixtures of truncated exponentials
av: Romero, Vanessa, et al.
Publicerad: (2017) -
Parameter Estimation in Mixtures of Truncated Exponentials
av: Langseth, Helge, et al.
Publicerad: (2012)