EAA Web Session ‚Addressing Class Imbalance in Machine Learning‘

In both life and general insurance, many predictive modelling tasks involve outcomes that occur infrequently—such as policy lapses, claims, or fraud. This leads to class imbalance, a situation where the target variable’s classes are not represented equally in the data, often with one class (e.g. policy lapse) being vastly outnumbered by the other. If not properly addressed, class imbalance can result in misleading classification models that overlook rare but critical events.
Anmeldeschluss: 2025-10-30
Link: https://actuarial-academy.com/seminars/seminar?No=E0523