Operations and evaluation measures for learning possibilistic graphical models
type: Item
instance of: scholarly article
title: Operations and evaluation measures for learning possibilistic graphical models
zbMATH Open document ID: 1082.68600
DOI: 10.1016/S0004-3702(03)00024-9
author: Christian Borgelt
author: Rudolf Kruse
published in: Artificial Intelligence
publication date: 2006-02-07T00:00:00Z
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 5003901
zbMATH Keywords: Graphical models
zbMATH Keywords: Possibilistic networks
zbMATH Keywords: Learning from data
zbMATH Keywords: Evaluation measures
describes a project that uses: PULCinella
describes a project that uses: C4.5
MaRDI profile type: Publication
cites work: Q3198876
cites work: Q4420631
cites work: Graphical models. Methods for data analysis and mining
cites work: Learning Bayesian networks: The combination of knowledge and statistical data
cites work: Approximating discrete probability distributions with dependence trees
cites work: A Bayesian method for the induction of probabilistic networks from data
cites work: Structure identification in relational data
cites work: Q4139463
cites work: Q4039980
cites work: The context model: An integrating view of vagueness and uncertainty
cites work: Q4762210
cites work: MEASURES OF UNCERTAINTY AND INFORMATION BASED ON POSSIBILITY DISTRIBUTIONS
cites work: An Introduction to Spatial Point Processes and Markov Random Fields
cites work: Conjugate Gradient Acceleration of the EM Algorithm
cites work: Where do we stand on measures of uncertainty, ambiguity, fuzziness, and the like?
cites work: Q4002150
cites work: Q4835267
cites work: On the shortest spanning subtree of a graph and the traveling salesman problem
cites work: Q4734791
cites work: Q4382293
cites work: A Mathematical Theory of Communication
cites work: Q3358073
full work available at URL: s0004-3702(03)00024-9
OpenAlex ID: W2079927294
description: scientific article; zbMATH DE number 5003901