This paper introduces a new method to learn the probabilities defining a BBNs from databases with missing data. The intuition behind this method is close to the robust sensitivity analysis interpretation of probability; the method computes the extreme points of the set of possible distributions cons
โฆ LIBER โฆ
093018 (M10) Guidelines for corrective replacement based on low stochastic structure assumptions : Newby M.J., Coolen P.F.A., Statistical Research Paper No 10, Department of Actuarial Science and Statistics, City University, UK, 1997
- Publisher
- Elsevier Science
- Year
- 1997
- Tongue
- English
- Weight
- 92 KB
- Volume
- 20
- Category
- Article
- ISSN
- 0167-6687
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โฆ Synopsis
This paper introduces a new method to learn the probabilities defining a BBNs from databases with missing data. The intuition behind this method is close to the robust sensitivity analysis interpretation of probability; the method computes the extreme points of the set of possible distributions consistent with the available information and proceeds by refining this set as more information becomes available. This paper outlines the description of this method and presents some experimental results comparing this approach to the Gibbs Samplings.
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093019 (M10) Approximations for the abso
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Article
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1997
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Elsevier Science
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English
โ 92 KB