Clustering data with the density-based method

As an alternative to distance measurement, you can use a density-based measurement to cluster data. This method finds an area with a higher density than the remaining area. One of the most famous methods is DBSCAN. In the following recipe, we will demonstrate how to use DBSCAN to perform density-based clustering.

Getting ready

In this recipe, we will use simulated data generated from the mlbench package.

How to do it...

Perform the following steps to perform density-based clustering:

  1. First, install and load the fpc and mlbench packages:
    > install.packages("mlbench")
    > library(mlbench)
    > install.packages("fpc")
    > library(fpc)
  2. You can then use the mlbench library to draw a Cassini problem graph:
    > set.seed(2) ...

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