code shares similarities with forestTrain.m but is optimized for binary
 labels. Moreover, while forestTrain is meant for training random decision
 forests, this code is tuned for use with boosting (see adaBoostTrain.m).

 For more information on how to quickly boost decision trees see:
   [1] R. Appel, T. Fuchs, P. Dollár, P. Perona; &quot;Quickly Boosting
   Decision Trees – Pruning Underachieving Features Early,&quot; ICML 2013.
 The code here implements a simple brute-force strategy with the option t