235 search results - page 23 / 47 » Compiling Bayesian Networks Using Variable Elimination |
UAI
2000
13 years 8 months ago
2000
In many domains, we are interested in analyzing the structure of the underlying distribution, e.g., whether one variable is a direct parent of the other. Bayesian model selection a...
IDEAL
2000
Springer
13 years 11 months ago
2000
Springer
Quantization of continuous variables is important in data analysis, especially for some model classes such as Bayesian networks and decision trees, which use discrete variables. Of...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
AODE (Aggregating One-Dependence Estimators) is considered one of the most interesting representatives of the Bayesian classifiers, taking into account not only the low error rate...
UAI
2001
13 years 9 months ago
2001
Many real life domains contain a mixture of discrete and continuous variables and can be modeled as hybrid Bayesian Networks (BNs). An important subclass of hybrid BNs are conditi...
UAI
2004
13 years 9 months ago
2004
Although many real-world stochastic planning problems are more naturally formulated by hybrid models with both discrete and continuous variables, current state-of-the-art methods ...