159 search results - page 1 / 32 » Bayesian Networks Optimization Based on Induction Learning T... |
IFIP12
2008
13 years 6 months ago
2008
Obtaining a bayesian network from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper, we define an automatic learni...
KDD
1999
ACM
13 years 8 months ago
1999
ACM
Tree Augmented Naive Bayes (TAN) has shown to be competitive with state-of-the-art machine learning algorithms [3]. However, the TAN induction algorithm that appears in [3] can be...
ML
2010
ACM
13 years 2 months ago
2010
ACM
In several domains it is common to have data from different, but closely related problems. For instance, in manufacturing, many products follow the same industrial process but with...
ICML
2009
IEEE
14 years 5 months ago
2009
IEEE
This paper addresses exact learning of Bayesian network structure from data and expert's knowledge based on score functions that are decomposable. First, it describes useful ...
FUIN
2008
13 years 3 months ago
2008
Causal relations are present in many application domains. Causal Probabilistic Logic (CP-logic) is a probabilistic modeling language that is especially designed to express such rel...