.child      - [Kx1] index of child for each node (1-indexed)
   .hs         - [Kx1] log ratio (.5*log(p/(1-p)) at each node
   .weights    - [Kx1] total sample weight at each node
   .depth      - [Kx1] depth of each node
  data       - data used for training tree (quantized version of input)
  err        - decision tree training error

 EXAMPLE

 See also <a href="binaryTreeApply.html" class="code" title="function hs = binaryTreeApply( X, tree, maxDepth, minWeight, nThreads )">binaryTreeApply</a>, <a href=