A hybrid self-supervised model predicting life satisfaction in South Korea.

ABSTRACT:

Objective

Life satisfaction pertains to an individual's subjective evaluation of their life quality, grounded in their personal criteria. It stands as a crucial cognitive aspect of subjective wellbeing, offering a reliable gauge of a person's comprehensive wellbeing status. In this research, our objective is to develop a hybrid self-supervised model tailored for predicting individuals' life satisfaction in South Korea.

Methods

We employed the Busan Metropolitan City Social Survey Data in 2021, a comprehensive dataset compiled by the Big Data Statistics Division of Busan Metropolitan City. After preprocessing, our analysis focused on a total of 32,390 individuals with 51 variables. We developed the self-supervised pre-training TabNet model as a key component of this study. In

SUBMITTER: Nguyen HV 

PROVIDER: S-EPMC11524807 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature