which averaging should be used when computing the ROC AUC on imbalanced data set?
<p>I am doing a binary classification task on imbalanced data set .. and right now computing the ROC AUC using : 
<code>sklearn.metrics.roc_auc_score(y_true, y_score, average='macro')</code> <a href="http://scikit-learn.org/stable/modules/generated/sklearn.metrics.roc_auc_score.html" rel="nofollow">source</a>
and I have two questions: </p>

<ul>
<li>I am not sure if the averaging <code>macro</code> is influenced by the class imbalance here and what is the best averaging in this situation (when classifying imbalanced classes)?</li>
<li>Is there a reference for the way that shows how scikit-learn calculate the ROC AUC with the different averaging argument ? </li>
</ul>

<p>The average='weighted' is your choice for the problem of imbalanced classes
as it follows from 3.3.2.1 in</p>

<blockquote>
  <p><a href="http://scikit-learn.org/stable/modules/model_evaluation.html" rel="nofollow">http://scikit-learn.org/stable/modules/model_evaluation.html</a></p>
</blockquote>

python machine-learning scikit-learn