title: LibSVM: -wi option (weight selection) during cross-validation and testing
body: <p>I need help about the weight option of libSVM. I'm confused at some point; should we also use the -wi option while doing cross-validation? If so, should we use the calculated weights of the whole data or the calculated weights according to the v-1 subsets (for v-fold cross-validation)? And my second question is should we use -wi option during predict? If so, should we use the calculated weights during training or should we calculate the weights according to the distribution of negative and positive instances in the test data? </p>
  
  <p>For example; we have 50 + data and 200 - data. So after calculating the best c and gamma parameter values we will use -w1 4 -w-1 1 options while training. But what about training during grid search and cross validation? Let's say we are performing 5-fold cross-validation. While training on each remaining 4 subsets, the distribution of negative and possitive instances will probably change. So should we recalculate the weights during this 5-fold cross validation?</p>
  
  <p>Besides shoud we use -w1 4 -w-1 1 options while testing?</p>
  
  <p>Thanks</p>