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Exploration and analysis of socio-economic and health data from 167 countries using MATLAB. Application of clustering algorithms to identify development patterns, visualize disparities, and understand global trends.
The objective of this study is to cluster the countries using socio-economic and health factors that determine the overall development of the country and to characterize each resulting cluster (and, consequently, the countries it comprises) based on the relevant values of the above factors
Analytical and computational exploration of clustering algorithms, focusing on k-means and k-medians, with MATLAB implementations and synthetic dataset analyses.