title: vowpal wabbit for binary text classification setup
body: <p>I am using vw-8.20170116 for a binary text classification problem.  The text strings are concatenated from several short (5-20 words) strings. The input looks like</p>
  
  <pre><code>-1 1.0 |aa .... ... ..... |bb ... ... .... .. |cc ....... .. ...
   1 5.0 |aa .... ... ..... |bb ..... .. .... . |cc .... .. ...
  </code></pre>
  
  <p>The command that I am using for training is</p>
  
  <pre><code>./vw-8.20170116 -d train_feat.txt -k -c -f model.vw --ngram 2 --skips 2 --nn 10 --loss_function logistic --passes 100 --l2 1e-8 --holdout_off --threads --ignore bc
  </code></pre>
  
  <p>and for test</p>
  
  <pre><code>./vw-8.20170116 -d test_feat.txt -t --loss_function logistic --link logistic -i model.vw -p test_pred.txt
  </code></pre>
  
  <p>Question:  How can I get vw to run (train) in parallel on my 8-core machine?  I thought --threads should help but I am not seeing any speedups.  And how do I control the number of cores used?</p>
  
  <p>Using this <a href="https://stats.stackexchange.com/questions/156722/vowpal-wabbit-best-strategy-for-short-text-data-like-titles-kewords">link</a> for reference.</p>