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ICML
2005
IEEE
16 years 3 months ago
Discriminative versus generative parameter and structure learning of Bayesian network classifiers
In this paper, we compare both discriminative and generative parameter learning on both discriminatively and generatively structured Bayesian network classifiers. We use either ma...
Franz Pernkopf, Jeff A. Bilmes
PAKDD
2000
ACM
161views Data Mining» more  PAKDD 2000»
15 years 6 months ago
Adaptive Boosting for Spatial Functions with Unstable Driving Attributes
Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
Aleksandar Lazarevic, Tim Fiez, Zoran Obradovic
ICML
2005
IEEE
16 years 3 months ago
Learning class-discriminative dynamic Bayesian networks
In many domains, a Bayesian network's topological structure is not known a priori and must be inferred from data. This requires a scoring function to measure how well a propo...
John Burge, Terran Lane
ICDM
2010
IEEE
147views Data Mining» more  ICDM 2010»
15 years 25 days ago
Subgroup Discovery Meets Bayesian Networks -- An Exceptional Model Mining Approach
Whenever a dataset has multiple discrete target variables, we want our algorithms to consider not only the variables themselves, but also the interdependencies between them. We pro...
Wouter Duivesteijn, Arno J. Knobbe, Ad Feelders, M...
CHI
2008
ACM
16 years 3 months ago
Invoking emotional support in a health crisis
This dissertation research explores the invocation of emotional support from friends and family for parents who have a baby in a Neonatal Intensive Care Unit, through the use of t...
Wendy Moncur