Definition
Density-based clusters are dense areas in the data space separated from each other by sparser areas. Furthermore, the density within the areas of noise is lower than the density in any of the clusters. Formalizing this intuition, for each core point the neighborhood of radius Eps has to contain at least MinPts points, i.e., the density in the neighborhood has to exceed some threshold. A point q is directly-density-reachable from a core point p if q is within the Eps-neighborhood of p, and density-reachability is given by the transitive closure of direct density-reachability. Two points p and q are called density-connected if there is a third point o from which both p and q are density-reachable. A cluster is then a set of density-connected points which is maximal with respect to density-reachability. Noiseis defined as the set of points in the database not belonging to any of its clusters. The task of density-based clustering is to find all clusters with respect to...
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Ester, M. (2018). Density-Based Clustering. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_605
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