Density-based spatial clustering of applications with noise (DBSCAN) is a data clustering algorithm proposed by Martin Ester, Hans-Peter Kriegel, Jörg Sander, and Xiaowei Xu in 1996. It is a density-based clustering algorithm that does not assume a fixed parametric model for the clusters, such as Gaussian blobs, and it does not require the number of clusters to be specified in advance.
Density-based spatial clustering of applications with noise (DBSCAN) is a data clustering algorithm proposed by Martin Ester, Hans-Peter Kriegel, Jörg Sander, and Xiaowei Xu in 1996. It is a density-based clustering algorithm that does not assume a fixed parametric model for the clusters, such as Gaussian blobs, and it does not require the number of clusters to be specified in advance.
Source: Wikipedia "DBSCAN" · CC BY-SA 4.0
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