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R Data Analysis Cookbook - Second Edition by Kuntal Ganguly

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Density-based clustering uses the idea of density reachability and density connectivity, which makes it very useful in discovering a cluster in nonlinear shapes. Density-based clustering takes two parameters into account--eps and MinPts. The eps parameter stands for the maximum radius of the neighborhood; MinPts denotes the minimum number of points within the eps neighborhood. Some of the common terminology associated with DBSCAN algorithm is as follows:

A point A in the dataset, with a neighbor count greater than or equal to MinPts, is referred to as a core point. The point A is called a border point if the number of its neighbors is less than MinPts, but belongs to the ϵ-neighborhood of some core point C. Finally, if a point ...

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