DBSCAN Clustering vs. k-Means Clustering The essence of the DBSCAN algorithm is to initialize a cluster that has a minimum number of points close to each other, and then expand outwards, looking for ...

In incremental approach, the DBSCAN algorithm is applied to a dynamic database where the data may be frequently updated. After insertions or deletions to the dynamic database, the clustering ...