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...
Glavni autori: | Pérez-Bernabé, Inmaculada, Salmerón Cerdán, Antonio, Langseth, Helge |
---|---|
Format: | info:eu-repo/semantics/article |
Jezik: | English |
Izdano: |
2017
|
Online pristup: | http://hdl.handle.net/10835/4859 |
Slična djela
-
Learning Mixtures of Truncated Basis Functions from Data
od: Langseth, Helge, i dr.
Izdano: (2017) -
Mixtures of Truncated Basis Functions
od: Langseth, Helge, i dr.
Izdano: (2017) -
MoTBFs: An R Package for Learning Hybrid Bayesian Networks Using Mixtures of Truncated Basis Functions
od: Maldonado González, Ana Devaki, i dr.
Izdano: (2023) -
Learning hybrid Bayesian networks using mixtures of truncated exponentials
od: Romero, Vanessa, i dr.
Izdano: (2017) -
Parameter Estimation in Mixtures of Truncated Exponentials
od: Langseth, Helge, i dr.
Izdano: (2012)