title: Multilabel classification using H20.ai (Driverless ai)
body: <br>
     We are testing out the capabilities of driverless AI. One of our first datasets is like this.
  X1,X2.... X400, Y1,Y2...Y200 <br>
  Here we want to do multi-label classification on our dataset.
  However, in the driverless AI web client, there is only an option to specify only one target. <br/>
  <p>Another alternative , I tried was concating all the Y variables into a single list.
  <a href="https://i.stack.imgur.com/3569r.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/3569r.png" alt="enter image description here" /></a> <br>
  However, instead of predicting each Y variable, h20.ai just treats every sequence of number as a class.<br>
  Like if there was 3 Y variables.<br>
  then [0 0 1] and [0 1 0] and so on till 8 classes.<br> Then while training, it just complains that some of these 8 classes dont have enough rows and drops them. In my case, i have over 200 Y variables, so it drops a lot of these classes.</p>
  <p>Does anyone know of any solution to do this in driverless AI?</p>
  <p>Thanks</p>