The DBSCAN algorithm classifies data points into three categories based on two parameters: neighborhood radius ($\epsilon$) and minimum points ($min\_samples$).

• Core Point: A point with at least $min\_samples$ points within its $\epsilon$-neighborhood.
• Border Point: A point within $\epsilon$ distance of a core point, but with fewer than $min\_samples$ neighbors itself.
• Noise: A point that is neither a core point nor a border point.