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123
Voted
ICPR
2008
IEEE
16 years 5 months ago
2008
IEEE
When a large amount of data are missing, or when multiple hidden nodes exist, learning parameters in Bayesian networks (BNs) becomes extremely difficult. This paper presents a lea...
135
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CIKM
1997
Springer
15 years 8 months ago
1997
Springer
This paper presents an efficient algorithm for learning Bayesian belief networks from databases. The algorithm takes a database as input and constructs the belief network structur...
154
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BMCBI
2008
15 years 3 months ago
2008
Background: Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mecha...
178
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JAISE
2010
14 years 10 months ago
2010
Studying human activities has significant implication in human beneficial applications such as personal healthcare. This research has been facilitated by the development of sensor ...
167
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UAI
1998
15 years 5 months ago
1998
In this paper we address the problem of discretization in the context of learning Bayesian networks (BNs) from data containing both continuous and discrete variables. We describe ...