Bayesian Network Structure Learning Based On Rough Set and Mutual Information
In Bayesian network structure learning for incomplete data set, a common problem is too many attributes causing low efficiency and high computation complexity. In this paper, an algorithm of attribute reduction based on rough set is introduced. The algorithm can effectively reduce the dimension of a...
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| Main Authors: | , , |
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| Format: | EJournal Article |
| Published: |
Institute of Advanced Engineering and Science,
2014-02-01.
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| Subjects: | |
| Online Access: | Get fulltext |
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| Summary: | In Bayesian network structure learning for incomplete data set, a common problem is too many attributes causing low efficiency and high computation complexity. In this paper, an algorithm of attribute reduction based on rough set is introduced. The algorithm can effectively reduce the dimension of attributes and quickly determine the network structure using mutual information for Bayesian network structure learning. DOI : http://dx.doi.org/10.11591/telkomnika.v12i2.3768 |
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