title: Meaning of correctly classified instances weka
body: <p>I recently started using weka and I'm trying to classify tweets into positive or negative using Naive Bayes. So I have a training set with tweets that I gave the label for and a test set with tweets that all have the label "positive". When I ran Naive Bayes, I get the following results:</p>
  
  <p>Correctly classified instances:     69 92%
  Incorrectly classified instances:   6   8%</p>
  
  <p>Then if I change the labels of the tweets in the test set to "negative" and ran again Naive Bayes, the results are inversed:</p>
  
  <p>Correctly classified instances:     6   8%
  Incorrectly classified instances:   69  92%</p>
  
  <p>I thought that correctly classified instances show the accuracy of Naive Bayes and that it should be the same no matter the labels of the tweets in test set. Is there something wrong with my data or I don't understand correctly the meaning of correctly classified instances?</p>
  
  <p>Thanks a lot for your time,</p>
  
  <p>Nantia</p>