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Mixtures of bayesian networks with decision graphs 원문보기

IPC분류정보
국가/구분 United States(US) Patent 등록
국제특허분류(IPC7판)
  • G06N-003/02
출원번호 US-0220200 (1998-12-23)
발명자 / 주소
  • Bo Thiesson
  • Christopher A. Meek
  • David Maxwell Chickering
  • David Earl Heckerman
출원인 / 주소
  • Microsoft Corporation
대리인 / 주소
    Michaelson & Wallace
인용정보 피인용 횟수 : 64  인용 특허 : 0

초록

One aspect of the invention is the construction of mixtures of Bayesian networks. Another aspect of the invention is the use of such mixtures of Bayesian networks to perform inferencing. A mixture of Bayesian networks (MBN) consists of plural hypothesis-specific Bayesian networks (HSBNs) having poss

대표청구항

1. A method in a computer system for constructing a mixture of Bayesian networks (MBN), for use in assisting a user in a decision-making process based upon a set of observed data, said (MBN) comprising plural hypothesis-specific Bayesian networks, (HSBNs) having network nodes, each of said network n

이 특허를 인용한 특허 (64)

  1. Rish, Irina; Tesauro, Gerald James, Active sampling collaborative prediction method for end-to-end performance prediction.
  2. Przytula,Krzysztof W., Apparatus, method, and computer program product for converting decision flowcharts into decision probabilistic graphs.
  3. Skaaning, Claus; Jensen, Finn V.; Kj.ae butted.rulff, Uffe; Pelletier, Paul A.; Jensen, Lasse Rostrup; Parker, Marilyn A.; Boborad, Janice L., Automated diagnosis of printer systems using Bayesian networks.
  4. Skaanning, Claus; Jensen, Finn V.; Kjærulff, Uffe; Pelletier, Paul A.; Jensen, Lasse Rostrup; Parker, Marilyn A.; Bogorad, Janice L., Automated diagnosis of printer systems using bayesian networks.
  5. Gansner, Harvey L., Automated legal evaluation using bayesian network over a communications network.
  6. Meek, Christopher A.; Heckerman, David E.; Rounthwaite, Robert L.; Chickering, David Maxwell; Thiesson, Bo, Bayesian approach for learning regression decision graph models and regression models for time series analysis.
  7. Wright, David J.; Bush, Gregory S.; Falb, David M., Bayesian classifier system using a non-linear probability function and method thereof.
  8. Woronow, Alex; Love, Karen M., Bayesian network triads for geologic and geophysical applications.
  9. Rippel, Steven P.; Birchall, James T.; Hess, III, John A.; Fresher, Brad Robert; Shipman, Mark Philip, Computerized sysem and method for data acquistion and application of disparate data to two stage bayesian networks to generate centrally maintained portable driving score data.
  10. Dirac, Leo Parker; Brueckner, Michael; Herbrich, Ralf, Concurrent binning of machine learning data.
  11. Edgar, Marc Thomas; Johnson, Christopher Donald, Cross correlation tool for automated portfolio descriptive statistics.
  12. Edgar, Marc Thomas; Johnson, Christopher Donald, Cross correlation tool for automated portfolio descriptive statistics.
  13. Evans-Beauchamp, Lincoln T.; Link, Jeremy, Decision engine and method and applications thereof.
  14. Bocharov, Alexei V.; Chickering, David M.; Heckerman, David E., Detecting instabilities in time series forecasting.
  15. Takeuchi, Jun-Ichi; Barron, Andrew R., Device, method, and medium for predicting a probability of an occurrence of a data.
  16. Coleman, Barry; McCarry, Frank, Dynamic display of web page content based on a rules system.
  17. Gerber, Martin T.; Rondoni, John C., Efficacy visualization.
  18. Thiesson, Bo; Meek, Christopher A., Efficient gradient computation for conditional Gaussian graphical models.
  19. Sandoval, Michael; Boardman, David Bradley; Downs, Oliver Bruce, Electronic profile development, storage, use, and systems therefor.
  20. Przytula, Krzysztof W.; Dash, Denver, Evaluation of Bayesian network models for decision support.
  21. Anderson, Mark Stephen; Engelhardt, Dean Crawford; Marriott, Damian Andrew; Randhawa, Suneel Singh, Event handling system.
  22. Dirac, Leo Parker; Agarwal, Tarun, Feature processing recipes for machine learning.
  23. Dirac, Leo Parker; Correa, Nicolle M.; Dannaker, Charles Eric, Feature processing tradeoff management.
  24. Heckerman, David E.; Chickering, D. Maxwell; Platt, John C.; Meek, Christopher A.; Thiesson, Bo, Goal-oriented clustering.
  25. Thiesson,Bo; Meek,Christopher A., Gradient learning for probabilistic ARMA time-series models.
  26. Lee, Sung-Ju; Banerjee, Sujata; Sharma, Puneet; Basu, Sujoy, Identifying a service node in a network.
  27. Dirac, Leo Parker; Correa, Nicolle M.; Ingerman, Aleksandr Mikhaylovich; Krishnan, Sriram; Li, Jin; Puvvadi, Sudhakar Rao; Zarandioon, Saman, Machine learning service.
  28. Johnson,Christopher Donald; Keyes,Tim Kerry; Edgar,Marc Thomas; Pisupati,Chandrasekhar; Steward,William Cree, Methods and apparatus for automated underwriting of segmentable portfolio assets.
  29. Goldberg, Roman; Rozenwald, Guy; Gottlieb, Amit; Harel, Amir, Multiple workspace database engine.
  30. Parikh,Prashant; Peters,Stanley, Navigation in a hierarchical structured transaction processing system.
  31. Parikh,Prashant; Peters,Stanley, Navigation in a hierarchical structured transaction processing system.
  32. Parikh,Prashant, Navigational learning in a structured transaction processing system.
  33. Farnham, Christopher, Objective decision making application using bias weighting factors.
  34. Yerramalla, Sampath K.; Donat, William; Rajamani, Ravi, Partitioning of turbomachine faults.
  35. Gerber, Martin T.; Rondoni, John C., Patient-individualized efficacy rating.
  36. Sandoval, Michael; Jonas, Joseph, Platform for data aggregation, communication, rule evaluation, and combinations thereof, using templated auto-generation.
  37. Kairo, Suzanne; Heins, William A.; Love, Karen M., Predicting sand-grain composition and sand texture.
  38. Downs, Oliver B.; Sandoval, Michael; Branzan, Claudiu Alin; Iovanov, Vlad Mircea; Khalsa, Sopurkh Singh, Providing recommendations using information determined for domains of interest.
  39. Downs, Oliver B.; Sandoval, Michael; Branzan, Claudiu Alin; Iovanov, Vlad Mircea; Khalsa, Sopurkh Singh, Providing recommendations using information determined for domains of interest.
  40. Johnson,Christopher Donald; Keyes,Tim Kerry; Spencer,David Jonathan; Midkiff,Catharine Lynn; Messmer,Richard Paul; Pisupati,Chandrasekhar; Chen,Yu to; Edgar,Marc Thomas; Cifarelli,James Louis; Akbay,, Rapid valuation of portfolios of assets such as financial instruments.
  41. D'Ambrosio, Bruce Douglass, Relational Bayesian modeling for electronic commerce.
  42. Bohacs, Kevin M.; West, Brian P.; Grabowski, George J., Retrodicting source-rock quality and paleoenvironmental conditions.
  43. Goetz,Steven M., Selection of neurostimulator parameter configurations using bayesian networks.
  44. Goetz, Steven M., Selection of neurostimulator parameter configurations using decision trees.
  45. Goetz, Steven M., Selection of neurostimulator parameter configurations using decision trees.
  46. Goetz,Steven M., Selection of neurostimulator parameter configurations using genetic algorithms.
  47. Goetz,Steven M., Selection of neurostimulator parameter configurations using neural network.
  48. Goetz, Steven M., Selection of neurostimulator parameter configurations using neural networks.
  49. Thiesson,Bo; Meek,Christopher A.; Heckerman,David E., Staged mixture modeling.
  50. Meek, Christopher A.; Chickering, David M.; Bernhardt, Jeffrey R.; Rounthwaite, Robert L., System and method for approximating probabilities using a decision tree.
  51. Guralnik,Valerie; Mylaraswamy,Dinkar; Voges,Harold C., System and method for combining diagnostic evidences for turbine engine fault detection.
  52. Moore, Peter; Pleshakov, Andrey, System and method for utilizing a logical graphical model for scenario analysis.
  53. Vassilvitskii, Sergei; Ravikumar, Shanmugasundaram; Bahmani, Bahman, Systems and methods for generating a dense graph.
  54. Meek,Christopher A.; Chickering,David M.; Weare,Christopher B.; Gupta,Pradeep K., Systems and methods for optimizing decision graph collaborative filtering.
  55. Sandoval, Michael; Downs, Oliver Bruce, Systems, methods, and computer readable media for security in profile utilizing systems.
  56. Gerber, Martin T.; Rondoni, John C., Tree-based electrical stimulator programming.
  57. Gerber, Martin T.; Rondoni, John C., Tree-based electrical stimulator programming.
  58. Rondoni, John C.; Gerber, Martin T., Tree-based electrical stimulator programming.
  59. Gerber, Martin T.; Rondoni, John C., Tree-based electrical stimulator programming for pain therapy.
  60. Dirac, Leo Parker; Jenatton, Rodolphe, Tuning software execution environments using Bayesian models.
  61. Mathias, Keith Eugene; Nixon, Mark Robert; Talbot, Patrick James, Uncertainty management in a decision-making system.
  62. Ringer, Maurice, Use of general bayesian networks in oilfield operations.
  63. Chickering,David M., Using tables to learn trees.
  64. Bishop, Christopher; Winn, John; Spiegelhalter, David J., Variational inference engine for probabilistic graphical models.
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