Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/1FA4C9A6-4931-4606-901C-F7E43F935E59 | ||
| Year | 2005 | ||
| Type of Item | Conference Short Paper | ||
| License |
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| Bibliographic Citation | L. Tsironis, H. Mavropoulos, V. Moustakis, T. Kontogiannis, "Mining Aberrant Driving Behavior Characteristics, WSEAS Transactions on Information Science and Applications," στο διεθνές συνέδριο WSEAS, Κέρκυρα, Ελλάδα, 2005. | ||
| Appears in Collections |
This article demonstrates the contribution of machine learning in modelingof aberrant driving characteristics. We demonstrate how machine learning can bedeployed to identify, classify, and model interesting and useful knowledge patterns,which are hidden in self reported replies to a Driving Behavior Questionnaire.Demonstration is based on empirical results drawn from 1453 responders in Greece.Experimentation was based on two machine learning approaches: decision treelearning and association rule mining and learning focused on the exact drivercharacteristics thought to be responsible for an accident to occur. Accuracy of resultswas assessed using randomized testing
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