Improving mortality forecasting using a hybrid of Lee–Carter and stacking ensemble model
Samuel Asante Gyamerah,
Aaron Akyea Mensah,
Clement Asare
et al.
Abstract:Background
Mortality forecasting is a critical component in various fields, including public health, insurance, and pension planning, where accurate predictions are essential for informed decision-making. This study introduces an innovative hybrid approach that combines the classical Lee–Carter model with advanced machine learning techniques, particularly the stack ensemble model, to enhance the accuracy and efficiency of mortality forecasts.
Results
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