Learning Bayesian networks from data: An information-theory based approach
Top Cited Papers
- 12 March 2002
- journal article
- Published by Elsevier in Artificial Intelligence
- Vol. 137 (1-2) , 43-90
- https://doi.org/10.1016/s0004-3702(02)00191-1
Abstract
No abstract availableKeywords
This publication has 24 references indexed in Scilit:
- Efficient reasoningACM Computing Surveys, 2001
- Reply to Humphreys and Freedman's Review of Causation, Prediction, and SearchThe British Journal for the Philosophy of Science, 1997
- A guide to the literature on learning probabilistic networks from dataIEEE Transactions on Knowledge and Data Engineering, 1996
- Learning Bayesian networks: The combination of knowledge and statistical dataMachine Learning, 1995
- Model Selection and Accounting for Model Uncertainty in Graphical Models Using Occam's WindowJournal of the American Statistical Association, 1994
- LEARNING BAYESIAN BELIEF NETWORKS: AN APPROACH BASED ON THE MDL PRINCIPLEComputational Intelligence, 1994
- A Bayesian method for the induction of probabilistic networks from dataMachine Learning, 1992
- An Algorithm for Fast Recovery of Sparse Causal GraphsSocial Science Computer Review, 1991
- Approximating discrete probability distributions with dependence treesIEEE Transactions on Information Theory, 1968
- On Information and SufficiencyThe Annals of Mathematical Statistics, 1951