If you like DBSCAN, I would recommend checking out OPTICS. It is not a clustering algorithm per se, but generates information from which clusterings for multipl

If you like DBSCAN, I would recommend checking out OPTICS. It is not a clustering algorithm per se, but generates information from which clusterings for multiple settings of DBSCAN parameters can be "queried" cheaply. The DBSCAN and OPTICS papers share an author. One my favorite algorithms. This is the original paper - [1], and this looks like a helpful presentation on the topic - [2]. Since you mention k-means, I would point out that unlike k-means which finds convex-shaped clusters only, DBSCAN/OPTICS identify clusters of any shape. [1] http://www.dbs.ifi.lmu.de/Publikationen/Papers/OPTICS.pdf http://www.dbs.ifi.lmu.de/Publikationen/Papers/OPTICS.pdf [2] https://www.cse.buffalo.edu/faculty/azhang/cse601/density-based.ppt https://www.cse.buffalo.edu/faculty/azhang/cse601/density-ba...