377 search results - page 15 / 76 » Learning Bayesian networks from data: An information-theory ... |
IJAR
2007
13 years 7 months ago
2007
The use of several types of structural restrictions within algorithms for learning Bayesian networks is considered. These restrictions may codify expert knowledge in a given domai...
KDD
2002
ACM
14 years 8 months ago
2002
ACM
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
ICML
2001
IEEE
14 years 8 months ago
2001
IEEE
Hard disk drive failures are rare but are often costly. The ability to predict failures is important to consumers, drive manufacturers, and computer system manufacturers alike. In...
FUZZIEEE
2007
IEEE
14 years 2 months ago
2007
IEEE
—Approaches based on conditional independence tests are among the most popular methods for learning graphical models from data. Due to the predominance of Bayesian networks in th...
DAWAK
2006
Springer
13 years 11 months ago
2006
Springer
Abstract. There is an urgent need for sound approaches to integrative and collaborative analysis of large, autonomous (and hence, inevitably semantically heterogeneous) data source...