title: Impact of unlabelled instances in model construction (Neural network) in Weka
body: <p>Two situations:</p>
  
  <ol>
  <li>I have a set of instances with label "0", "1", and "?". I use the labelled ones (1,0) to train a multilayer perceptron (default settings, SMOTE correction, LOOCV to estimate performance), build a model and then predict the "?" instances. </li>
  <li>I use all instances (1, 0, ?) to train the NN (default settings, SMOTE correction for imbalance between 1 and 0 instances, as before, and LOOCV to estimate performance). </li>
  </ol>
  
  <p>Scores given to each prediction change between both situations. </p>
  
  <p>My question is, how does NN handle having unlabelled instances in the training set? Is situation 1 a bad approach?</p>
  
  <p>thanks</p>