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Incremental Learning of Bayesian Networks with Hidden Variables
San Jose, California November 29-December 02
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDM.2001.989594First IEEE International Conference o ...
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Fengzhan Tian, Hongwei Zhong, Yuchang Lu, Chunyi Shi, "Incremental Learning of Bayesian Networks with Hidden Variables," Data Mining, IEEE International Conference on, pp. 651, First IEEE International Conference on Data Mining (ICDM'01), 2001.
 
 
BibTex
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@article{ 10.1109/ICDM.2001.989594,
author = {Fengzhan Tian and Hongwei Zhong and Yuchang Lu and Chunyi Shi},
title = {Incremental Learning of Bayesian Networks with Hidden Variables},
journal ={Data Mining, IEEE International Conference on},
volume = {0},
year = {2001},
isbn = {0-7695-1119-8},
pages = {651},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICDM.2001.989594},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Data Mining, IEEE International Conference on
TI - Incremental Learning of Bayesian Networks with Hidden Variables
SN - 0-7695-1119-8
SP
EP
A1 - Fengzhan Tian,
A1 - Hongwei Zhong,
A1 - Yuchang Lu,
A1 - Chunyi Shi,
PY - 2001
VL - 0
JA - Data Mining, IEEE International Conference on
ER -
 
In this paper, an incremental method for learning Bayesian networks based on evolutionary computing, IEMA, is put forward. IEMA introduces the evolutionary algorithm and EM algorithm into the process of incremental learning, can not only avoid getting into local maxima, but also incrementally learn Bayesian networks with high accuracy in presence of missing values and hidden variables. In addition, we improved the incremental learning process by Friedman et al. The experimental results verified the validity of IEMA. In terms of storage cost, IEMA is comparable with the incremental learning method of Friedman et al, while it is ore accurate.
Citation:
Fengzhan Tian, Hongwei Zhong, Yuchang Lu, Chunyi Shi, "Incremental Learning of Bayesian Networks with Hidden Variables," icdm, pp.651, First IEEE International Conference on Data Mining (ICDM'01), 2001
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