title: Random Forest with p>>n and not enough memory
body: <p>I am trying to perform Random Forest classification on genomic data with ~200k predictors and ~20 rows. Predictors have been already pruned for autocorrelation. I tried to use the 'ranger' R package, but it complains it cannot allocate  164Gb vector (I do have 32Gb RAM).</p>
  <ol>
  <li>Is there any RF implementation that can manage the analysis given
  the available RAM (I would like to avoid increasing the swap)?</li>
  <li>Should I maybe use a different algorithm (for what I read, RF should
  deal alright with p&gt;&gt;n)?</li>
  </ol>