An AI-based Model to Measure World Happiness using Vector Quantization Methodology

Happiness is undeniably an important aspect to look at while analyzing the state of an individual or a group. The governments of numerous countries have begun to develop their citizens' happiness indices after realizing the significant impact of happiness on their country's growth rate. To analyze the correlations between numerous happiness index elements and to establish a categorization scheme for 156 countries, we applied the K-means clustering technique to the World Happiness Report. The world's nations are classified into three distinct clusters, reflecting low, medium, and high levels of happiness, and graphical analysis is implemented to demonstrate the relationships between various global factors that influence the happiness index.