Learning Bayesian networks: The combination of knowledge and statistical data

Learning Bayesian networks: The combination of knowledge and statistical data (1995)

by David Heckerman , David M. Chickering

Venue:	Machine Learning
Citations:	752 - 29 self

Datum	Value	Source
TITLE	Learning Bayesian networks: The combination of knowledge and statistical data	INFERENCE
AUTHOR NAME	David Heckerman	SVM HeaderParse 0.2
AUTHOR AFFIL	Dan Geiger ∗ Microsoft Research, Bldg 9S	SVM HeaderParse 0.2
AUTHOR ADDR	Redmond, WA 98052-6399	SVM HeaderParse 0.2
AUTHOR NAME	David M. Chickering	SVM HeaderParse 0.2
ABSTRACT	We describe scoring metrics for learning Bayesian networks from a combination of user knowledge and statistical data. We identify two important properties of metrics, which we call event equivalence and parameter modularity. These properties have been mostly ignored, but when combined, greatly simplify the encoding of a user’s prior knowledge. In particular, a user can express his knowledge—for the most part—as a single prior Bayesian network for the domain. 1	SVM HeaderParse 0.2
YEAR	1995	INFERENCE
VENUE	Machine Learning	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	20--197	INFERENCE
CITATIONS	2 found	ParsCit 1.0