title: Stratified sampling for Random forest -Python
body: <p>I'm building a random forest classification model with the response variable split being 98%(False)-2%(True). I'm using Scikit Learn's RandomForest classifier for this. </p>
  
  <p>What is the best way to handle this unbalanced data and avoid oversampling?</p>