Invention Grant
- Patent Title: Conditional probability tables for Bayesian belief networks
- Patent Title (中): 贝叶斯信念网络的条件概率表
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Application No.: US11656085Application Date: 2007-01-22
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Publication No.: US08170977B2Publication Date: 2012-05-01
- Inventor: Zachary T. Cox , Jonathan Pfautz , David Koelle , Geoffrey Catto , Joseph Campolongo
- Applicant: Zachary T. Cox , Jonathan Pfautz , David Koelle , Geoffrey Catto , Joseph Campolongo
- Applicant Address: US MA Cambridge
- Assignee: Charles River Analytics, Inc.
- Current Assignee: Charles River Analytics, Inc.
- Current Assignee Address: US MA Cambridge
- Agency: McDermott Will & Emery LLP
- Main IPC: G06F9/44
- IPC: G06F9/44 ; G06N7/02

Abstract:
An apparatus for making probabilistic inferences based on a belief network includes a processing system configured to receive as input one or more parameters of a causal influence model. The belief network has a child node Y and one or more parent nodes Xi (i=1, . . . , n) for the child node Y. The causal influence model describes the influence of the parent nodes Xi on possible states of the child node Y. The processing system is further configured to use a creation function to convert the parameters of the causal influence model into one or more entries of a conditional probability table. The conditional probability table provides a probability distribution for all the possible states of the child node Y, for each combination of possible states of the parent nodes Xi.
Public/Granted literature
- US20080177679A1 Conditional probability tables for Bayesian belief networks Public/Granted day:2008-07-24
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