Leveraging Mean Shift and Spectral Clustering: A Study on Crime Patterns in Los Angeles

In an era marked by growing complexity and interconnectivity, addressing crime is paramount for the well-being of communities worldwide. This study utilises Los Angeles Crime Data to employ clustering algorithms which are Mean Shift and Spectral Clustering, unravelling intricate crime patterns, and aiding proactive law enforcement strategies. Analysing a subset of 458,452 records from 2010 to 2019, this research identifies crime hotspots, clusters areas with similar crime trends, and extracts valuable insights into crime dynamics. Results reveal distinct patterns in crime occurrence, enabling efficient resource allocation and targeted interventions by law enforcement agencies.