Two-Dimensional DBSCAN Clustering Algorithm with Implementation Details

A density-based clustering algorithm for 2D data that takes (x,y) coordinate arrays, search radius Eps, and density threshold Minpts as inputs. The implementation outputs clusters in array format where each row represents a cluster containing the original dataset IDs of its member points, with additional code-level insights about neighborhood search and cluster expansion mechanisms.