Volume : III, Issue : IX, September - 2013

An Efficient Technique for Privacy Preserving Decision Tree Learning

Dr. S. Vijayarani, M. Sangeetha

Abstract :

Data mining helps to extract hidden predictive information from large databases. There are several techniques and algorithms used for extracting the hidden patterns from the large data sets and finding the relationships between them. Privacy preservation is an important factor in data mining. 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. This approach converts the original sample datasets into a group of unreal datasets. The original sample datasets cannot be reconstructed from it. Meanwhile, an accurate decision tree is built using those unreal datasets. C4.5 algorithm is used to build decision tree. The experimental results show that accurate and efficient decision tree is built in C4.5 algorithm than existing algorithm.  

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Article: Download PDF   DOI : 10.36106/ijar  

Cite This Article:

Dr. S.Vijayarani, M. Sangeetha An Efficient Technique for Privacy Preserving Decision Tree Learning Indian Journal of Applied Research, Vol.III, Issue.IX September 2013

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