Brendan Tierney takes us through the DBScan algorithm:
Let’s illustrate the use of DBScan (Density Based Spatial Clustering of Applications with Noise), using the scikit-learn Python package, for a “manufactured” dataset. This example will illustrate how this density based algorithm works (See my other blog post which compares different Clustering algorithms for this same dataset). DBSCAN is better suited for datasets that have disproportional cluster sizes (or densities), and whose data can be separated in a non-linear fashion.
Click through for an interesting read on a dataset which is historically difficult to cluster (unless you know the general shape and translate everything to polar coordinates).