machine learning approach for best location of retailers

This paper presents a machine learning approach using the k-means clustering algorithm to identify optimal locations for retailers. the study aims to leverage geographic, demographic, and economic factors to cluster potential locations and provide valuable insights for decision-making. the methodology involves data preparation, selecting relevant features, applying the k-means algorithm, evaluating cluster results, and visualizing the outcomes on a map. numerical results demonstrate the effectiveness of the proposed approach in identifying suitable retail locations. the study concludes with a summary of findings and recommendations for further research.