# binaryTreeApply

## PURPOSE

Apply learned binary decision tree classifier.

## SYNOPSIS

function hs = binaryTreeApply( X, tree, maxDepth, minWeight, nThreads )

## DESCRIPTION

     Apply learned binary decision tree classifier.

     USAGE
      hs = binaryTreeApply( X, tree, [maxDepth], [minWeight], [nThreads] )

     INPUTS
      X          - [NxF] N length F feature vectors
      tree       - learned tree classification model
      maxDepth   - [] maximum depth of tree
      minWeight  - [] minimum sample weigth to allow split
      nThreads   - [inf] max number of computational threads to use

     OUTPUTS
      hs         - [Nx1] predicted output log ratios

     EXAMPLE

     See also binaryTreeTrain

     Piotr's Image&Video Toolbox      Version 3.21
     Copyright 2013 Piotr Dollar.  [pdollar-at-caltech.edu]
     Please email me if you find bugs, or have suggestions or questions!
     Licensed under the Simplified BSD License [see external/bsd.txt]