A Tutorial on Learning Bayesian Networks

A Tutorial on Learning Bayesian Networks (1995)

by David Heckerman

Venue:	Communications of the ACM
Citations:	247 - 11 self

Datum	Value	Source
TITLE	A tutorial on learning bayesian networks	INFERENCE
AUTHOR NAME	David Heckerman	SVM HeaderParse 0.1
AUTHOR AFFIL	Microsoft Research; Advanced Technology Division; Microsoft Corporation	SVM HeaderParse 0.2
AUTHOR ADDR	One Microsoft Way; Redmond, WA	SVM HeaderParse 0.1
ABSTRACT	We examine a graphical representation of uncertain knowledge called a Bayesian network. The representation is easy to construct and interpret, yet has formal probabilistic semantics making it suitable for statistical manipulation. We show how we can use the representation to learn new knowledge by combining domain knowledge with statistical data. 1	SVM HeaderParse 0.1
YEAR	1995	INFERENCE
VENUE	Communications of the ACM	INFERENCE
VENUE TYPE	TECHREPORT	INFERENCE
VOLUME	38	INFERENCE
TECH	Technical Report MSR-TR-95-06, Microsoft Research	INFERENCE
CITATIONS	81 found	ParsCit 1.0