title: Cross Validation in Weka
body: <p>I've always thought from what I read that cross validation is performed like this:</p>
  
  <blockquote>
    <p>In k-fold cross-validation, the original sample is randomly
    partitioned into k subsamples. Of the k subsamples, a single subsample
    is retained as the validation data for testing the model, and the
    remaining k − 1 subsamples are used as training data. The
    cross-validation process is then repeated k times (the folds), with
    each of the k subsamples used exactly once as the validation data. The
    k results from the folds then can be averaged (or otherwise combined)
    to produce a single estimation</p>
  </blockquote>
  
  <p>So k models are built and the final one is the average of those.
  In Weka guide is written that each model is always built using ALL the data set. So how does cross validation in Weka work ? Is the model built from all data and the "cross-validation" means that k fold are created then each fold is evaluated on it and the final output results is simply the averaged result from folds?</p>