Journal of Computer Sciences and Applications
ISSN (Print): 2328-7268 ISSN (Online): 2328-725X Website: Editor-in-chief: Minhua Ma, Patricia Goncalves
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Journal of Computer Sciences and Applications. 2015, 3(3), 61-66
DOI: 10.12691/jcsa-3-3-1
Open AccessArticle

Transplanting Binary Decision Trees

Eli M. Dow1, and Tim Penderghest2,

1IBM / Clarkson University, Potsdam NY, USA

2Clarkson University, Potsdam NY, USA

Pub. Date: May 04, 2015

Cite this paper:
Eli M. Dow and Tim Penderghest. Transplanting Binary Decision Trees. Journal of Computer Sciences and Applications. 2015; 3(3):61-66. doi: 10.12691/jcsa-3-3-1


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, consultr. 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.

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