title: k-means empty cluster
body: <p>I try to implement <a href="http://en.wikipedia.org/wiki/K-means_clustering">k-means</a> as a homework assignment. My exercise sheet gives me following remark regarding empty centers:</p>
  
  <blockquote>
    <p>During the iterations, if any of the cluster centers has no data points associated with it, replace it with a random data point.</p>
  </blockquote>
  
  <p>That confuses me a bit, firstly Wikipedia or other sources I read do not mention that at all. I further read about a problem with 'choosing a good k for your data' - how is my algorithm supposed to converge if I start setting new centers for cluster that were empty.</p>
  
  <p>If I ignore empty clusters I converge after 30-40 iterations. Is it wrong to ignore empty clusters? </p>