title: vowpal-wabbit: use of multiple passes, holdout, & holdout-period to avoid overfitting?
body: <p>I would like to train the binary sigmoidal feedforward network for category classification with following command using awesome <code>vowpal wabbit tool</code>:</p>
  
  <pre><code>vw --binary --nn 4 train.vw -f category.model
  </code></pre>
  
  <p>And test it:</p>
  
  <pre><code>vw --binary -t -i category.model -p test.vw
  </code></pre>
  
  <p>But I had very bad results (comparing to my linear svm estimator).</p>
  
  <p>I found a comment that I should use <code>Number of Training Passes</code> argument (<code>--passes arg</code>).</p>
  
  <p>So my question is <strong>how to know the count of training passes in order not to get retrained model</strong>?</p>
  
  <p>P.S. should I use <code>holdout_period</code> argument? and how?      </p>