title: Comparing parallel k-means batch vs mini-batch speed
body: <p>I am trying to cluster 1000 dimension, 250k vectors using k-means. The machine that I am working on has 80 dual-cores.</p>
  
  <p>Just confirming, if anyone has compared the run-time of k-means default batch parallel version against k-means mini-batch version? The <a href="http://scikit-learn.org/stable/auto_examples/cluster/plot_mini_batch_kmeans.html#example-cluster-plot-mini-batch-kmeans-py" rel="noreferrer">example comparison page</a> on sklean documents doesn't provide much info as the dataset is quite small.  </p>
  
  <p>Much appreciate your help. </p>
  
  <p>Regards,</p>