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| Man Leung Wong, Wai Lam, Kwong Sak Leung, "Using Evolutionary Programming and Minimum Description Length Principle for Data Mining of Bayesian Networks," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 2, pp. 174-178, February, 1999. | |||
| BibTex | x | ||
| @article{ 10.1109/34.748825, author = {Man Leung Wong and Wai Lam and Kwong Sak Leung}, title = {Using Evolutionary Programming and Minimum Description Length Principle for Data Mining of Bayesian Networks}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {21}, number = {2}, issn = {0162-8828}, year = {1999}, pages = {174-178}, doi = {http://doi.ieeecomputersociety.org/10.1109/34.748825}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - JOUR JO - IEEE Transactions on Pattern Analysis and Machine Intelligence TI - Using Evolutionary Programming and Minimum Description Length Principle for Data Mining of Bayesian Networks IS - 2 SN - 0162-8828 SP174 EP178 EPD - 174-178 A1 - Man Leung Wong, A1 - Wai Lam, A1 - Kwong Sak Leung, PY - 1999 KW - Evolutionary computation KW - Bayesian networks KW - unsupervised learning KW - minimum description length principle KW - genetic algorithms. VL - 21 JA - IEEE Transactions on Pattern Analysis and Machine Intelligence ER - | |||
Abstract—We have developed a new approach (MDLEP) to learning Bayesian network structures based on the Minimum Description Length (MDL) principle and Evolutionary Programming (EP). 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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