Claims frequency modeling using telematics car driving data
Guangyuan Gao, Shengwang Meng and Mario V. Wüthrich
| Year of publication: |
2019
|
|---|---|
| Authors: | Gao, Guangyuan ; Meng, Shengwang ; Wüthrich, Mario V. |
| Published in: |
Scandinavian actuarial journal. - Stockholm : Taylor & Francis, ISSN 1651-2030, ZDB-ID 2029609-5. - Vol. 2019.2019, 2, p. 143-162
|
| Subject: | autoencoder | bottleneck neural network | car insurance pricing | claims frequency modeling | generalized additive model | K-means algorithm | Kullback-Leibler divergence | pattern recognition | principal components analysis | Telematics data | v-a heatmap | Theorie | Theory | Algorithmus | Algorithm | Neuronale Netze | Neural networks | Kraftfahrzeug | Motor vehicle | Kfz-Versicherung | Automobile insurance | Engpass | Bottleneck |
Online Resource
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1080/03461238.2018.1523068 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10012194942