title: sklearn: fitting RandomForestClassifier or normilize data with chunks of data
body: <p>I have a big file with training data. I am worry, when I use this code:</p>
  
  <pre><code>clf = RandomForestClassifier()
  for chunk in reader:
      clf.fit(chunk, target)
  </code></pre>
  
  <p>Do clf will produce model for all chunk or only for current? For incremental learning should I use only Classifiers with partial_fit() method? How I should normalize train data (build normalizer for whole data, neither only current chunk) in that way? </p>