Python, Clustering, Data Science, Machine Learning.
concept is to find clusters based on the density of points. DBSCAN identifies itself as the number of clusters, contrary to other popular clustering algorithm K-means. The behaviour of DBSCAN is controlled by setting two parameters: Epsilon (eps) which defines the radius of the neighbour around a