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...

תיאור מלא

מידע ביבליוגרפי

Principais autores:	Kwanda Sydwell Ngwenduna, Rendani Mbuvha
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	MDPI AG 2021-03-01
סדרה:	Risks
נושאים:	actuarial science class imbalance data augmentation generative models generative adversarial network synthetic sampling
גישה מקוונת:	https://www.mdpi.com/2227-9091/9/3/49
תגים:	הוספת תג אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!