@article{jcsa2015331,
author={{Dow, Eli M. and Penderghest, Tim},
title={Transplanting Binary Decision Trees},
journal={Journal of Computer Sciences and Applications},
volume={3},
number={3},
pages={61--66},
year={2015},
url={http://pubs.sciepub.com/jcsa/3/3/1},
issn={2328-725X},
abstract={In this paper, we describe a means of compiling binary decision trees as generated by the C4.5 binary decision tree classifier into high-performance, reusable, stand-alone, run-time classifiers. We demonstrate the memory savings and run time characteristics of a compiled tree as compared to the traditional use of a C4.5 runtime. We demonstrate 100% correctness over every input we have available for testing as compared to our own enhanced version of the classic C4.5 run-time classification routine, <i>consultr</i>. In addition, this work provides a framework for comparing decision tree classifiers to more in vogue classifiers such as support vector machines as demonstrated within.},
doi={10.12691/jcsa-3-3-1}
publisher={Science and Education Publishing}
}