title: What is the theorical foundation for scikit-learn dummy classifier?
body: <p>By the <a href="http://scikit-learn.org/stable/modules/generated/sklearn.dummy.DummyClassifier.html">documentation</a> I read that a dummy classifier can be used to test it against a classification algorithm.</p>
  
  <blockquote>
    <p>This classifier is useful as a simple baseline to compare with other
    (real) classifiers. Do not use it for real problems.</p>
  </blockquote>
  
  <p>What does the dummy classifier do when it uses the stratified aproach. I know that the docummentation says that:</p>
  
  <blockquote>
    <p>generates predictions by respecting the training set’s class
    distribution.</p>
  </blockquote>
  
  <p>Could anybody give me a more theorical explanation of why this is a proof for the performance of the classifier?.</p>