Machine Learning with R Cookbook - Second Edition

How it works...

Density-based clustering uses the idea of density reachability and density connectivity, which makes it very useful in discovering a cluster in nonlinear shapes. Before discussing the process of density-based clustering, some important background concepts must be explained. Density-based clustering takes two parameters into account: eps and MinPts. eps stands for the maximum radius of the neighborhood; MinPts denotes the minimum number of points within the eps neighborhood. With these two parameters, we can define the core point as having points more than MinPts within eps. Also, we can define the board point as having points less than MinPts, but it is in the neighborhood of the core points. Then, we can define the core object ...