Institutional Repository
Technical University of Crete
Technical University of Crete
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EL
| URI | http://purl.tuc.gr/dl/dias/1FA4C9A6-4931-4606-901C-F7E43F935E59 | - |
| Language | en | - |
| Title | Mining aberrant driving behavior characteristics | el |
| Creator | Moustakis Vasilis | en |
| Creator | Μουστακης Βασιλης | el |
| Creator | Tsironis Loukas | en |
| Creator | Τσιρωνης Λουκας | el |
| Creator | Kontogiannis Thomas | en |
| Creator | Κοντογιαννης Θωμας | el |
| Creator | H. Mavropoulos | en |
| Content Summary | This article demonstrates the contribution of machine learning in modeling of aberrant driving characteristics. We demonstrate how machine learning can be deployed 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 tree learning and association rule mining and learning focused on the exact driver characteristics thought to be responsible for an accident to occur. Accuracy of results was assessed using randomized testing | en |
| Type of Item | Σύντομη Δημοσίευση σε Συνέδριο | el |
| Type of Item | Conference Short Paper | en |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2015-11-05 | - |
| Date of Publication | 2005 | - |
| 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. | el |
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