title: class_weight = 'balanced' equivalent for naive bayes
body: <p>I'm performing some (binary)text classification with two different classifiers on the same unbalanced data. i want to compare the results of the two classifiers.</p>
  <p>When using sklearns logistic regression, I have the option of setting the <code>class_weight = 'balanced'</code> for sklearn naive bayes, there is no such parameter available.</p>
  <p>I know, that I can just randomly sample from the bigger class in order to end up with equal sizes for both classes, but then the data is lost.</p>
  <p>Why is there no such parameter for naive bayes? I guess it has something to do with the nature of the algorithm, but cant find anything about this specific matter. I also would like to know what the equivalent would be? How to achieve a similar effect (that the classifier is aware of the imbalanced data and gives more weight to the minority class and less to the majority class)?</p>