title: How to use your own custom classifier with sklearn's adaboost method?
body: <p>I have my own classifier which is written in python.
     I want to use that classifier with adaboostclassifier method.
     One example which has been provided online is in the <a href="http://scikit-learn.org/stable/auto_examples/ensemble/plot_adaboost_regression.html#example-ensemble-plot-adaboost-regression-py" rel="noreferrer">link</a>.</p>
  
  <p>The key code line is as follows</p>
  
  <pre><code>  clf_2 = AdaBoostRegressor(DecisionTreeRegressor(max_depth=4),
                        n_estimators=300, random_state=rng)
  </code></pre>
  
  <p>It combines the DecisionTreeRegressor with the boosting.</p>
  
  <p>I am wondering that how could we give the custom made classification method.</p>
  
  <p>Which methods are required to be implemented, data formats etc.</p>
  
  <p>Is there any code which could be followed online? 
     Any code sample which could demonstrate, plugging in your custom classifier.</p>