Automatic determination of the number of clusters by mixtures of bayesian networks
US6529891B1 · kind B1 · utility
124Cited by
5References
58Claims
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Key dates
| Filing date | Dec 23, 1998 |
| Grant date | Mar 4, 2003 |
| Priority date | — |
| Expiry date | Dec 23, 2018 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY10S707/99948
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The invention automatically determines the number of clusters in a Bayesian network or in a mixture of Bayesian networks (MBN). A common external hidden variable is associated with the network. Expected sufficient statistics (ESS) are computed in the case of a Bayesian network or expected complete model sufficient statistics (ECMSS) are computed in the case of an MBN, from the observed data. An expected sample size for each state of a hidden variable is computed from the ESS or ECMSS. The optimum number of states is reached by deleting those states having a sample size less than a predetermined threshold.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.