title: Running OPTICS algorithm on ELKI
body: <p>I'm normally an R user (a beginning R user, but I'm starting to get the hang of it). However, I have heard positive things about ELKI--in particular, its speed.  I came across this old post <a href="https://stackoverflow.com/questions/14695138/how-to-group-nearby-latitude-and-longitude-locations-stored-in-sql">"How to group nearby latitude and longitude locations stored in SQL"</a> and the answer posted by Anony-Mousse is similar to what I'd like to do. I would like to be able to replicate each step he has done up to the KML file he has shared on Google Drive.</p>
  
  <p>I've downloaded ELKI and am able to run the mini-GUI, which looks like the following:</p>
  
  <p><img src="https://i.stack.imgur.com/yprlR.png" alt="enter image description here"></p>
  
  <p>Could someone post some steps on how to do what Anony-Mousse was able to do?</p>
  
  <p>My data is very similar in nature.  I have geocoded addresses in a csv file (more specifically, each tuple is an event and one of the variables/features/columns is the geocoded address of the event) and I'm looking to find clusters much like the OP in the link above.</p>
  
  <p>Hopefully, Anony-Mousse will read this post and come to the rescue. But, I'd be grateful if anyone else could help get me on my way.</p>