The process shows, using the Compound dataset, the advantages of using density based clustering by using the DBSCAN clustering algorithm.
The dataset consist of 399 two-dimensional vectors belonging to six groups. The groups differ in the density of their points, and each set can encompass another point set as well.
The process yields remarkable results even with default settings, only one out of the six clusters contains an error. Using the parameters
min points, results can be refined further, but as the points in the above-mentioned cluster are of different densities, a perfect solution cannot be reached.
The operation of the DBSCAN algorithm has been demonstration on a dataset consisting of groups with different densities. The deficiencies of the algorithm have been shows, i.e. that if points of different densities can be found in a cluster, the precise operation of the algorithm cannot be guaranteed.