3 years ago

On Using Linear Diophantine Equations to Tune the extent of Look Ahead while Hiding Decision Tree Rules.

Dimitris Kalles, Vassilios S. Verykios, Georgios Feretzakis

This paper focuses on preserving the privacy of sensitive pat-terns when inducing decision trees. We adopt a record aug-mentation approach for hiding sensitive classification rules in binary datasets. Such a hiding methodology is preferred over other heuristic solutions like output perturbation or crypto-graphic techniques - which restrict the usability of the data - since the raw data itself is readily available for public use. In this paper, we propose a look ahead approach using linear Diophantine equations in order to add the appropriate number of instances while minimally disturbing the initial entropy of the nodes.

Publisher URL: http://arxiv.org/abs/1710.07214

DOI: arXiv:1710.07214v1

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