Predicting Motor Insurance Claims Using Telematics Data—XGBoost versus Logistic Regression

Predicting Motor Insurance Claims Using Telematics Data—XGBoost versus Logistic Regression

XGBoost is recognized as an algorithm with exceptional predictive capacity. Models for a binary response indicating the existence of accident claims versus no claims can be used to identify the determinants of traffic accidents. This study compared the relative performances of logistic regression an...

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Bibliographic Details
Main Authors: Jessica Pesantez-Narvaez, Montserrat Guillen, Manuela Alcañiz
Format: Article
Language:English
Published: MDPI AG 2019-06-01
Series:Risks
Subjects:
dichotomous response
predictive model
tree boosting
GLM
machine learning
Online Access:https://www.mdpi.com/2227-9091/7/2/70

Internet

https://www.mdpi.com/2227-9091/7/2/70

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