title: WEKA - Force the same classification distribution as the training set when testing
body: <p>I am using Weka (training various classifiers such as <em>SimpleLogistic, BayesNet</em>) for a 3 class classification problem. In my training set, my data takes the following class distribution:</p>
  
  <p><strong>Training set</strong></p>
  
  <ul>
  <li><strong>Class A:</strong> 50% of instances</li>
  <li><strong>Class B:</strong> 25% of instances</li>
  <li><strong>Class C:</strong> 25% of instances</li>
  </ul>
  
  <p>When I train various classification models I almost always get (roughly) the same classification distribution:</p>
  
  <p><strong>Test set predictions</strong></p>
  
  <ul>
  <li><strong>Class A:</strong> 60% of instances</li>
  <li><strong>Class B:</strong> 2% of instances</li>
  <li><strong>Class C:</strong> 38% of instances</li>
  </ul>
  
  <p>Class B is essentially never predicted by my models. </p>
  
  <p><strong>Question</strong> </p>
  
  <p>Is there a way in Weka to force the classifier to match the classification distribution as seen in the training set? 
  <em>(i.e. force a 50/25/25 classification distribution in my example)</em></p>