Automatic Generation of Bayesian networks in Forensic Science
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Constructing an effective and complete Bayesian network (BN) for individual cases that involve multiple related pieces of evidence and hypotheses requires a major investment of effort. Hence, generic BNs have been developed for common situations that only require adapting the underlying probabilities. This makes it practically possible to build and use BNs in casework. However, in some situations both the probability tables and the structure of the network depend on case specific details. For example, in crime linkage case the structure depends on the number of linked cases and the number of different pieces of evidence in each. We show it is possible to use R to generate both the structure and the underlying conditional probability tables. Furthermore, the entire work now can be performed from an online GUI without specialist software. Such a work now can reduce the workload for forensic statisticians and increase the mutual understanding between researchers and legal professionals. Automatic Generation of Bayesian networks in Forensic Science (PDF Download Available). Available from: https://www.researchgate.net/publication/322722134_Automatic_Generation_of_Bayesian_networks_in_Forensic_Science?channel=doi&linkId=5a6b3a130f7e9b1c12d1f762&showFulltext=true [accessed Feb 20 2018].
AuthorsFENTON, NE; DE ZOETE, J; 10th International Conference on Forensic Inference and Statistics
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