DBSCAN Density-Based Clustering

Density-based spatial clustering that automatically discovers clusters of arbitrary shape and size without pre-specifying the number of clusters (k). Identifies noise/outlier points and handles non-spherical cluster geometries that k-means cannot capture. Uses eps (neighborhood radius) and minPts (minimum points threshold) parameters. Suitable for spatial data, irregular cluster shapes, and outlier detection.