Boosting Poisson regression models with telematics car driving data

DOI10.1007/s10994-021-05957-0OpenAlexW3136214430MaRDI QIDQ2127229

Yanyan Li

Publication date: 20 April 2022

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-021-05957-0

zbMATH Keywords

Poisson regressiongeneralized linear modelregression treeconvolutional neural networkclaims frequency modelingcombined actuarial neural networkdensely connected feed-forward neural networktelematics car driving datatelematics heatmap

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (4)

What can we learn from telematics car driving data: a survey ⋮ Actuarial intelligence in auto insurance: claim frequency modeling with driving behavior features and improved boosted trees ⋮ Robust claim frequency modeling through phase-type mixture-of-experts regression ⋮ IMPROVING AUTOMOBILE INSURANCE CLAIMS FREQUENCY PREDICTION WITH TELEMATICS CAR DRIVING DATA

Uses Software

• R

Cites Work

• Unnamed Item
• Classification of scale-sensitive telematic observables for riskindividual pricing
• Actuarial Modelling of Claim Counts
• A data driven binning strategy for the construction of insurance tariff classes
• THE USE OF ANNUAL MILEAGE AS A RATING VARIABLE
• A Mathematical Theory of Deep Convolutional Neural Networks for Feature Extraction
• JOINT OPTIMIZATION OF TRANSITION RULES AND THE PREMIUM SCALE IN A BONUS-MALUS SYSTEM
• PREDICTIVE CLAIM SCORES FOR DYNAMIC MULTI-PRODUCT RISK CLASSIFICATION IN INSURANCE
• ADDRESSING IMBALANCED INSURANCE DATA THROUGH ZERO-INFLATED POISSON REGRESSION WITH BOOSTING
• Boosting Insights in Insurance Tariff Plans with Tree-Based Machine Learning Methods
• A POSTERIORI RATEMAKING WITH PANEL DATA
• Claims frequency modeling using telematics car driving data

This page was built for publication: Boosting Poisson regression models with telematics car driving data