# Generating Conditional Probabilities for Bayesian Networks: Easing the Knowledge Acquisition Problem

@article{Das2004GeneratingCP, title={Generating Conditional Probabilities for Bayesian Networks: Easing the Knowledge Acquisition Problem}, author={Balaram Das}, journal={ArXiv}, year={2004}, volume={cs.AI/0411034} }

The number of probability distributions required to populate a conditional probability table (CPT) in a Bayesian network, grows exponentially with the number of parent-nodes associated with that table. If the table is to be populated through knowledge elicited from a domain expert then the sheer magnitude of the task forms a considerable cognitive barrier. In this paper we devise an algorithm to populate the CPT while easing the extent of knowledge acquisition. The input to the algorithm… Expand

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