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ML
2010
ACM
151views Machine Learning» more  ML 2010»
13 years 5 months ago
Inductive transfer for learning Bayesian networks
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...
Roger Luis, Luis Enrique Sucar, Eduardo F. Morales
KDD
1994
ACM
123views Data Mining» more  KDD 1994»
13 years 11 months ago
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data
We describe scoring metrics for learning Bayesian networks from a combination of user knowledge and statistical data. We identify two important properties of metrics, which we cal...
David Heckerman, Dan Geiger, David Maxwell Chicker...
SBRN
2000
IEEE
13 years 11 months ago
Adaptation of Parameters of BP Algorithm Using Learning Automata
d Articles >> Table of Contents >> Abstract VI Brazilian Symposium on Neural Networks (SBRN'00) p. 24 Adaptation of Parameters of BP Algorithm Using Automata Hamid...
Hamid Beigy, Mohammad Reza Meybodi
ACL
2007
13 years 9 months ago
A fully Bayesian approach to unsupervised part-of-speech tagging
Unsupervised learning of linguistic structure is a difficult problem. A common approach is to define a generative model and maximize the probability of the hidden structure give...
Sharon Goldwater, Tom Griffiths
DKE
2007
95views more  DKE 2007»
13 years 7 months 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...