2012 Fiscal Year Final Research Report
Consistency of Bayesian Network Structure Learning
| Project/Area Number |
21500138
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Intelligent informatics
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| Research Institution | Osaka University |
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Principal Investigator |
SUZUKI Joe 大阪大学, 大学院・理学研究科, 准教授 (50216397)
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| Co-Investigator(Renkei-kenkyūsha) |
FUJIWARA Akio 大阪大学, 大学院・理学研究科, 教授 (30251359)
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| Project Period (FY) |
2009 – 2012
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| Keywords | ベイズネット / 情報量基準 / 一致性 / ガウシアン / 統計科学 |
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| Research Abstract |
This research address the problem of finding the true structure of a Baysian network (BN) from a finite sample of examples. In particular, we apply information criteria which is expressed by the sum of likelihood and complexity of the BN structure. If the latter is too stressed, we cannot obtain the true structure even if the number of examples grows. We found the condition that the true one is obtained with probability one, and proved it.
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[Presentation]2011
Author(s)
T. Inazumi, T. Washio, S. Shimizu, J.Suzuki, A. Yamamoto and Y. Kawahara
Organizer
Proc.UAI2011:The 27th Conf. on Uncertainty inArtificial Intelligence
Year and Date
2011-07-21
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