title: Stratified splitting train/test - H2O
body: <p>I use H2O to build and compare models but I wanted to know if there is a feature that allows me to split the data into train and test in a stratified way?</p>
  <p>I know that for cross validation the option fold_assignment exist and I use it.</p>
  <p>My question is more on the manipulation of the data and when it needs to be split before any model is built.</p>
  <p>I had a look a this <a href="http://docs.h2o.ai/h2o/latest-stable/h2o-docs/data-munging/splitting-datasets.html" rel="nofollow noreferrer">page</a> but it does not specify if stratified splitting is done for classification.</p>
  <p>Maybe for classification problems it is implicit and the stratified splitting is always achieved?</p>