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FLAIRS
2004
14 years 11 months ago
Mining Bayesian Networks to Forecast Adverse Outcomes Related to Acute Coronary Syndrome
One fascinating aspect of tool building for datamining is the application of a generalized datamining tool to a specific domain. Often times, this process results in a cross disci...
Andy Novobilski, Francis M. Fesmire, David Sonnema...
80
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UAI
2003
14 years 11 months ago
Learning Continuous Time Bayesian Networks
Continuous time Bayesian networks (CTBN) describe structured stochastic processes with finitely many states that evolve over continuous time. A CTBN is a directed (possibly cycli...
Uri Nodelman, Christian R. Shelton, Daphne Koller
AI
2002
Springer
14 years 10 months ago
Learning Bayesian networks from data: An information-theory based approach
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
SDM
2007
SIAM
120views Data Mining» more  SDM 2007»
14 years 11 months ago
An Analysis of Logistic Models: Exponential Family Connections and Online Performance
Logistic models are arguably one of the most widely used data analysis techniques. In this paper, we present analyses focussing on two important aspects of logistic models—its r...
Arindam Banerjee
UAI
1997
14 years 11 months ago
Robustness Analysis of Bayesian Networks with Local Convex Sets of Distributions
Robust Bayesian inference is the calculation of posterior probability bounds given perturbations in a probabilistic model. This paper focuses on perturbations that can be expresse...
Fabio Gagliardi Cozman