Journal Article10.1109/34.748825
Using evolutionary programming and minimum description length principle for data mining of Bayesian networks
TL;DR: A new approach to learning Bayesian network structures based on the minimum description length (MDL) principle and evolutionary programming is developed, which employs a MDL metric and integrates a knowledge-guided genetic operator for the optimization in the search process.
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Abstract: We have developed a new approach to learning Bayesian network structures based on the minimum description length (MDL) principle and evolutionary programming. It employs a MDL metric, which is founded on information theory, and integrates a knowledge-guided genetic operator for the optimization in the search process.
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Citations
Review: learning bayesian networks: Approaches and issues
TL;DR: This work takes a broad look at the literature on learning Bayesian networks—in particular their structure—from data, and hopes that all the major fields in the area are covered.
Machine Learning for Direct Marketing Response Models: Bayesian Networks with Evolutionary Programming
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Learning Bayesian networks: approaches and issues
S Tuart A Itken
- 01 Jan 2011
TL;DR: This work takes a broad look at the literature on learning Bayesian networks—in particular their structure—from data, and aims to locate all the relevant publications.
167
An efficient data mining method for learning Bayesian networks using an evolutionary algorithm-based hybrid approach
Man Leung Wong,Kwong-Sak Leung +1 more
TL;DR: A novel data mining approach that employs an evolutionary algorithm to discover knowledge represented in Bayesian networks is proposed, which outperforms MDLEP, the previous algorithm which uses evolutionary programming (EP) for network learning, and other network learning algorithms.
Structural learning of Bayesian networks by bacterial foraging optimization
TL;DR: The experimental results verify that the proposed BFO-B algorithm is a viable alternative to learn the structures of Bayesian networks, and is also highly competitive compared to state of the art algorithms.
54
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