title: Scaling data in scikit-learn SVM
body: <p>While libsvm provides tools for scaling data, with Scikit-Learn (which should be based upon libSVM for the SVC classifier) I find no way to scale my data. </p>
  
  <p>Basically I want to use 4 features, of which 3 range from 0 to 1 and the last one is a "big" highly variable number. </p>
  
  <p>If I include the fourth feature in libSVM (using the easy.py script which scales my data automatically) I get some very nice results (96% accuracy). 
  If I include the fourth variable in Scikit-Learn the accuracy drops to ~78% - but if I exclude it, I get the same results I get in libSVM when excluding that feature. Therefore I am pretty sure it's a problem of missing scaling.</p>
  
  <p>How do I replicate programmatically (i.e. without calling svm-scale) the scaling process of SVM?</p>