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Constructing Bayesian networks for criminal profiling from limited data

✍ Scribed by K. Baumgartner; S. Ferrari; G. Palermo

Book ID
108197542
Publisher
Elsevier Science
Year
2008
Tongue
English
Weight
578 KB
Volume
21
Category
Article
ISSN
0950-7051

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The problem of learning Bayesian networks from statistical data is described and reformulated as a discrete optimization problem. For a solution we employ the stochastic algorithm that is known as simulated annealing and that is based on the Markov Chain Monte Carlo approach. Numerical examples are