Presentation 2012-01-27
A Study on Approximate Probabilistic Reasoning Algorithm for Assuring and Correcting Accuracy Results on Bayesian Networks
Shuhei WAKASAKI, Daisuke KITAKOSHI, Masato SUZUKI,
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Abstract(in English) In this paper, we propose an approximate probabilistic reasoning algorithm using the connecting structures of Bayesian networks, known as one of the stochastic models. The proposed algorithm is composed of a number of existing reasoning algorithms, such as loopy-BP and conditioning, and two kinds of statistical techniques (hypothesis testing and interval estimate). We call this algorithm Extended LBPC (Ex-LBPC). Ex-LBPC can assure accuracy of reasoning results, and corrects the results when the results cannot be assured. Computer simulations are carried out to evaluate basic characteristics and performance of the proposed algorithm.
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Keyword(in English) Bayesian network / Loopy-BP / Conditioning / Sampling / Hypothesis Testing / Interval Estimation
Paper # NC2011-110
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Committee NC
Conference Date 2012/1/19(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) A Study on Approximate Probabilistic Reasoning Algorithm for Assuring and Correcting Accuracy Results on Bayesian Networks
Sub Title (in English)
Keyword(1) Bayesian network
Keyword(2) Loopy-BP
Keyword(3) Conditioning
Keyword(4) Sampling
Keyword(5) Hypothesis Testing
Keyword(6) Interval Estimation
1st Author's Name Shuhei WAKASAKI
1st Author's Affiliation Tokyo National College of Technology()
2nd Author's Name Daisuke KITAKOSHI
2nd Author's Affiliation Tokyo National College of Technology
3rd Author's Name Masato SUZUKI
3rd Author's Affiliation Tokyo National College of Technology
Date 2012-01-27
Paper # NC2011-110
Volume (vol) vol.111
Number (no) 419
Page pp.pp.-
#Pages 6
Date of Issue