Teacher(s)
Language
English
> French-friendly
> French-friendly
Prerequisites
Knowledge of English at the level of the LANGL1330 course.
LACTU2150 Analyse statistique des données d'assurance
LACTU2150 Analyse statistique des données d'assurance
Main themes
Classification and regression trees for claim propension, claim counts, claim severities and claim duration. Ensemble methods: Bagging, Random forests, Boosting. Applications to risk classification.
Content
Classification and regression trees for claim propension, claim counts, claim severities and claim duration. Ensemble methods: Bagging, Random forests, Boosting. Applications to risk classification
Teaching methods
The course consists of theoretical lessons illustrated with numerous practical cases in which students are required to participate.
Evaluation methods
Assessment is based on an individual report in which the methods covered during the lectures are applied to a real dataset. The report will be defended orally.
Online resources
Moodle website
Bibliography
Denuit, M., Hainaut, D., Trufin, J. (2020). Effective Statistical Learning Methods for Actuaries. Volume 2: Tree-Based Methods. Springer Actuarial Lecture Notes Series.
Faculty or entity
Programmes / formations proposant cette unité d'enseignement (UE)
Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Master [120] in Actuarial Science
