Volume : IV, Issue : III, March - 2014

A Novel Privacy Preserving Approach for Decision Tree Learning

Dr. S. Vijayarani, M. Sangeetha

Abstract :

Data mining is the extraction of the hidden information from large databases. Preserving privacy against data mining algorithms is a new research area. The problem of privacy preservation in data mining has become more important in recent years because of increasing need to store vast data about users. In this research work, a new privacy preserving approach is applied to decision tree learning. The original sample datasets are converted into a group of unreal datasets. An accurate decision tree is built using those unreal datasets. Many decision tree learning algorithms are used to generate decision tree such as CART, CHAID, and Ripper. In this research work, decision tree learning algorithms namely ID3 and C4.5 algorithms are used for building decision tree. A new modified decision learning approach is proposed for generating an accurate decision tree. The performance of the decision tree learning algorithms and the proposed technique are evaluated.

Keywords :

Article: Download PDF   DOI : 10.36106/ijar  

Cite This Article:

Dr. S.Vijayarani, M.Sangeetha A Novel Privacy Preserving Approach for Decision Tree Learning Indian Journal of Applied Research, Vol.IV, Issue. III

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