26 search results - page 5 / 6 » Learning the Bayesian Network Structure: Dirichlet Prior vs ... |
ECSQARU
2005
Springer
13 years 10 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...
BMCBI
2011
13 years 9 days ago
2011
Background: The combination of genotypic and genome-wide expression data arising from segregating populations offers an unprecedented opportunity to model and dissect complex phen...
ISDA
2008
IEEE
13 years 11 months ago
2008
IEEE
Gene network reconstruction is a multidisciplinary research area involving data mining, machine learning, statistics, ontologies and others. Reconstructed gene network allows us t...
ECSQARU
2001
Springer
13 years 9 months ago
2001
Springer
Abstract. The K2 metric is a well-known evaluation measure (or scoring function) for learning Bayesian networks from data [7]. It is derived by assuming uniform prior distributions...
CSB
2003
IEEE
13 years 10 months ago
2003
IEEE
Cluster methods have been successfully applied in gene expression data analysis to address tumor classification. By grouping tissue samples into homogeneous subsets, more systema...