title: Scikit-learn balanced subsampling
body: <p>I'm trying to create N balanced random subsamples of my large unbalanced dataset. Is there a way to do this simply with scikit-learn / pandas or do I have to implement it myself? Any pointers to code that does this?</p>
  
  <p>These subsamples should be random and can be overlapping as I feed each to separate classifier in a very large ensemble of classifiers.</p>
  
  <p>In Weka there is tool called spreadsubsample, is there equivalent in sklearn? 
  <a href="http://wiki.pentaho.com/display/DATAMINING/SpreadSubsample">http://wiki.pentaho.com/display/DATAMINING/SpreadSubsample</a></p>
  
  <p>(I know about weighting but that's not what I'm looking for.)</p>