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Write a short note on DBSCAN.
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  • DBSCAN (Density-Based Spatial Clustering of Applications with Noise) is a density based clustering algorithm.
  • The algorithm groups regions with sufficiently high density into clusters and discovers clusters of arbitrary shape in spatial databases with noise.
  • It defines a cluster as a maximal set of density-connected points.
  • Density = number of points within a specified radius (Eps)
  • A point is a core point if it has more than specified number of points (Min Pts) within Eps
  • Core point is in the interior of a cluster
  • A border point has fewer than Min Pts within Eps but is in neighborhood of a core point
  • A noise point is any point that is neither a core point nor a border point.

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