Describe the issue linked to the documentation

As seen here:
https://scikit-learn.org/stable/tutorial/machine_learning_map/index.html

One of the "tough luck" paths that go through the clustering section appear to say this is the case when there are >10k samples.

Suggest a potential alternative/fix

However, with modern computational hardware, and the optimized implementation of DBSCAN in Scikit-learn, it appears that it may be helpful to recommend DBSCAN as a possible solution for datasets containing <100K or even <1M datapoints for clustering in reasonable amounts of time on CPU.