Paper Info
Title
Learning imprecise probability models: Conceptual and practical challenges.
Abstract
The paper by Masegosa and Moral, on “Imprecise probability models for learning multinomial distributions from data”, considers the combination of observed data and minimal prior assumptions so as to produce possibly interval-valued parameter estimates. We offer an evaluation of Masegosa and Moral's proposals.
Year
DOI
Venue
2014
10.1016/j.ijar.2014.04.016
International Journal of Approximate Reasoning
Keywords
DocType
Volume
Imprecise probabilities,Multinomial learning,Credal networks
Journal
55
Issue
ISSN
Citations 
7
0888-613X
2
PageRank 
References 
Authors
0.38
2
1
Name
Order
Citations
PageRank
Fábio Cozman11810.16