title: R Random Forests Variable Importance
body: <p>I am trying to use the random forests package for classification in R.</p>
  
  <p>The Variable Importance Measures listed are:</p>
  
  <ul>
  <li>mean raw importance score of variable x for class 0</li>
  <li>mean raw importance score of variable x for class 1</li>
  <li><code>MeanDecreaseAccuracy</code></li>
  <li><code>MeanDecreaseGini</code></li>
  </ul>
  
  <p>Now I know what these "mean" as in I know their definitions.  What I want to know is how to use them.</p>
  
  <p>What I really want to know is what these values mean in only the context of how accurate they are, what is a good value, what is a bad value, what are the maximums and minimums, etc.</p>
  
  <p>If a variable has a high <code>MeanDecreaseAccuracy</code> or <code>MeanDecreaseGini</code> does that mean it is important or unimportant?  Also any information on raw scores could be useful too.
  I want to know everything there is to know about these numbers that is relevant to the application of them.  </p>
  
  <p>An explanation that uses the words 'error', 'summation', or 'permutated' would be less helpful then a simpler explanation that didn't involve any discussion of how random forests works.</p>
  
  <p>Like if I wanted someone to explain to me how to use a radio, I wouldn't expect the explanation to involve how a radio converts radio waves into sound.</p>