title: Vowpal Wabbit multiple class classification predict probabilities
body: <p>I am trying to do multiple classification problem with Vowpal Wabbit.</p>
  
  <p>I have a train file that look like this:</p>
  
  <p>1 |feature_space</p>
  
  <p>2 |feature_space</p>
  
  <p>3 |feature_space</p>
  
  <p>As an output I want to get probabilities of test item belonging to each class, like this:</p>
  
  <p>1: 0.13 2:0.57 3:0.30</p>
  
  <p>think of sklearn classifiers predict_proba methods, for example.</p>
  
  <p>I've tried the following:</p>
  
  <p>1) vw -oaa 3 train.file -f model.file --loss_function logistic --link logistic
  vw -p predict.file -t test.file -i model.file -raw_predictions = pred.txt</p>
  
  <p>but the pred.txt file is empty (contains no records, but is created). Predict.file contains only the final class, and no probabilities.</p>
  
  <p>2) vw - csoaa3 train.file -f model.file --link logistic
  I've modified the input files accordingly to fit the cs format. csoaa doesn't accept loss_function logistic with following error message: "You are using a label not -1 or 1 with a loss function expecting that!"</p>
  
  <p>If used with default square loss function, and similar output command, I get pred.txt with raw predictions for each class per item, for example:</p>
  
  <p>2.33 1.67 0.55</p>
  
  <p>I believe it's the resulting square distance.</p>
  
  <p>Is there a way to get VW to output class probabilites or somehow convert these distances into probabilities? </p>