Modelling Road Accidents: an Empirical Comparison of Algorithms for Learning Bayesian Networks
نویسندگان
چکیده
The paper presents the first results of the BayWay (Bayesian Roadway) project by providing an empirical comparison of some algorithms for intelligent data mining and Bayesian network learning on artificial road accident datasets. We outline the theoretical motivations of the project, deal with the problems involved in the construction of statistical models of road accidents, and introduce our hybrid approach (MIDA). The machine learning algorithms and the artificial datasets used in the comparison are then presented. We illustrate the methodology and the metrics utilized in the experiment, and describe the main results. The paper ends by drawing some general conclusions about the techniques to be used for mining road accident datasets.
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