506 search results - page 17 / 102 » Learning Bayesian Networks from Incomplete Databases |
JMLR
2010
13 years 5 months ago
2010
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
JASIS
2000
13 years 10 months ago
2000
s In data mining, we emphasize the need for learning from huge, incomplete and imperfect data sets (Fayyad et al. 1996, Frawley et al. 1991, Piatetsky-Shapiro and Frawley, 1991). T...
BIOCOMP
2006
14 years 12 days ago
2006
To improve the recovery of gene-gene and marker-gene (eQTL) interaction networks from microarray and genetic data, we propose a new procedure for learning Bayesian networks. This a...
ECSQARU
2005
Springer
14 years 4 months ago
2005
Springer
In this paper we explore the use of several types of structural restrictions within algorithms for learning Bayesian networks. These restrictions may codify expert knowledge in a g...
ICDAR
2009
IEEE
13 years 8 months ago
2009
IEEE
Combining classifier methods have shown their effectiveness in a number of applications. Nonetheless, using simultaneously multiple classifiers may result in some cases in a reduc...