
doi: 10.1002/wics.48
AbstractBayesian networks are defined, and the chain rule for Bayesian networks is stated. Outlines of algorithms provided: inference in Bayesian networks, sensitivity analysis, EM for parameter learning, and learning structure. Copyright © 2009 John Wiley & Sons, Inc.This article is categorized under:Statistical and Graphical Methods of Data Analysis > Bayesian Methods and Theory
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 31 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
