Alleviating Class Imbalance in Actuarial Applications Using Generative Adversarial Networks

Alleviating Class Imbalance in Actuarial Applications Using Generative Adversarial Networks

To build adequate predictive models, a substantial amount of data is desirable. However, when expanding to new or unexplored territories, this required level of information is rarely always available. To build such models, actuaries often have to: procure data from local providers, use limited unsui...

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Bibliographic Details
Main Authors: Kwanda Sydwell Ngwenduna, Rendani Mbuvha
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Risks
Subjects:
actuarial science
class imbalance
data augmentation
generative models
generative adversarial network
synthetic sampling
Online Access:https://www.mdpi.com/2227-9091/9/3/49

Internet

https://www.mdpi.com/2227-9091/9/3/49

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