A METHOD FOR ASSESSING PERSONAL WELL-BEING BASED ON FITNESS DATA

Authors

L.K. ANDREASYAN National Polytechnic University of Armenia Author

Keywords:

fitness data, supervised and unsupervised machine learning, bivariate Archimedean copula functions

Abstract

To assess the well-being of an individual and grouping according to health status, an analysis of the real data collected by smart watches using supervised and unsupervised machine learning algorithms is carried out and the dependence between important indicators selected from the grouping data using bivariate Archimedean copula functions is assessed.

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Published

11.11.2024

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