COST-SENSITIVE MULTI-CLASS ADABOOST FOR UNDERSTANDING DRIVING BEHAVIOR BASED ON TELEMATICS

Boosting Poisson regression models with telematics car driving data

(2021) Guangyuan Gao et al.   MACHINE LEARNING

Classification of Kidney Cancer Data Using Cost-Sensitive Hybrid Deep Learning Approach

(2020) Ho Sun Shon et al.   Symmetry-Basel

Cost-Sensitive KNN Classification

(2019) Shichao Zhang   NEUROCOMPUTING

Improving imbalanced learning through a heuristic oversampling method based on k-means and SMOTE

(2018) Georgios Douzas et al.   INFORMATION SCIENCES

Improving automobile insurance ratemaking using telematics: incorporating mileage and driver behaviour data

(2018) Mercedes Ayuso et al.   TRANSPORTATION

Claims frequency modeling using telematics car driving data

(2018) Guangyuan Gao et al.   Scandinavian Actuarial Journal

Multi-class AdaBoost

(2013) Trevor Hastie et al.   Statistics and Its Interface

A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches

(2011) M. Galar et al.   IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND RE

RUSBoost: A Hybrid Approach to Alleviating Class Imbalance

(2009) Chris Seiffert et al.   IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS

SVMs Modeling for Highly Imbalanced Classification

(2008) Yuchun Tang et al.   IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS