title: Parameter oob_score_ in scikit-learn equals accuracy or error?
body: <p>I implemented Random Forest classifiers (RF) from Python scikit-learn package for a ML problem. In the first stage I used cross validation to spot check other algorithms and RF is now my choice.</p>
  <p>Later on I also checked out what the OOB estimation of RF tells me. However, when I compare the return in 'oob_score_' with my results from CV I have a large discrepancy.</p>
  <p>The scikit-learn doc tells me:</p>
  <blockquote>
  <p>oob_score : bool</p>
  <p>Whether to use out-of-bag samples to estimate the generalization error.</p>
  </blockquote>
  <p>Because of the doc I was assuming that the Parameter 'oob_score_' is the error estimation. But looking for reasons it also came to my mind that it might actually estimate the accuracy instead This would be - at least a bit - closer to my CV results. I checked also the code, and more believe it's the accuracy but wanted to be sure... (in this case I find the doc misleading BTW).</p>
  <p>Is oob_score_ in scikit-learn accuracy or error estimation?</p>