title: Density based clustering that allows user to specify number of clusters
body: <p>I have data that consists of roughly 100,000 points on a 2-d graph. Each point has X and Y coordinates. I'm looking for an algorithm that will cluster these points based on density but I want to specify the number of clusters.</p>
  <p>I originally tried K-Means since this would allow me to specify the number of clusters. However, my data naturally &quot;clumps&quot; into ridges. K-Means would inevitably bisect some of these ridges. DBSCAN seems like a better fit simply due to the shape of my data, but with DBSCAN I can't specify the number of clusters I'd like.</p>
  <p>Essentially what I'm trying to find is an algorithm that will optimally cluster the graph into N groups based on density. Where N is supplied by me. At this point I don't care where it's implemented (R, Python, FORTRAN...).</p>
  <p>Any direction you can provide would be much appreciated.</p>