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DKE
2007
95views more  DKE 2007»
15 years 15 days ago
Strategies for improving the modeling and interpretability of Bayesian networks
One of the main factors for the knowledge discovery success is related to the comprehensibility of the patterns discovered by applying data mining techniques. Amongst which we can...
Ádamo L. de Santana, Carlos Renato Lisboa F...
FLAIRS
2009
14 years 10 months ago
Constraint-based Approach to Discovery of Inter Module Dependencies in Modular Bayesian Networks
This paper introduces an information theoretic approach to verification of modular causal probabilistic models. We assume systems which are gradually extended by adding new functi...
Patrick de Oude, Gregor Pavlin
JMLR
2010
125views more  JMLR 2010»
14 years 7 months ago
Continuous Time Bayesian Network Reasoning and Learning Engine
We present a continuous time Bayesian network reasoning and learning engine (CTBN-RLE). A continuous time Bayesian network (CTBN) provides a compact (factored) description of a co...
Christian R. Shelton, Yu Fan, William Lam, Joon Le...
IJPRAI
2000
83views more  IJPRAI 2000»
15 years 10 days ago
Practical Issues in Modeling Large Diagnostic Systems with Multiply Sectioned Bayesian Networks
As Bayesian networks become widely accepted as a normative formalism for diagnosis based on probabilistic knowledge, they are applied to increasingly larger problem domains. These...
Yanping Xiang, Kristian G. Olesen, Finn Verner Jen...
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LION
2009
Springer
129views Optimization» more  LION 2009»
15 years 7 months ago
Expeditive Extensions of Evolutionary Bayesian Probabilistic Neural Networks
Abstract. Probabilistic Neural Networks (PNNs) constitute a promising methodology for classification and prediction tasks. Their performance depends heavily on several factors, su...
Vasileios L. Georgiou, Sonia Malefaki, Konstantino...