106 search results - page 2 / 22 » The max-min hill-climbing Bayesian network structure learnin... |
GECCO
2007
Springer
13 years 11 months ago
2007
Springer
Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7]....
ICDAR
2009
IEEE
13 years 3 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...
BMCBI
2011
12 years 9 months ago
2011
Background: Protein secondary structure prediction provides insight into protein function and is a valuable preliminary step for predicting the 3D structure of a protein. Dynamic ...
IJAR
2007
13 years 5 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...
AIIA
2003
Springer
13 years 10 months ago
2003
Springer
A bayesian network is an appropriate tool for working with uncertainty and probability, that are typical of real-life applications. In literature we find different approaches for b...