Publication Type:

Journal Article

Source:

Journal of Advanced Research in Dynamical and Control Systems, Volume 9, Issue 02, p.1059-1067 (2017)

URL:

http://www.jardcs.org/backissues/abstract.php?archiveid=582

Abstract:

With the recent advancement in technology and supreme power to store large amounts of data invokes the endless possibilities of data mining and analysis using Data Warehouses and Cloud Storage.Peta bytes of data being generatedismaking the countries/companies/industries/organisations data driven which, decides the trends and finds the hidden patterns, with better visualisation. With data comes the important issue and aspect of maintenance its privacy. Privacy preserving in data mining is an upcoming field of research which is using various statistical and state of the art machine learning algorithm for preserving the very sensitive information about the firms from Data Miners while still allowing them to find the useful rules. In this paper we propose a way for maintaining our data secrecy using Linear Regression which uses Genetic Algorithm for deciding over the features for the most optimised accuracy and higher secrecy levels.

Cite this Research Publication

Kumaran U. and Neelu Khare, “Feature Selection for Privacy Preserving in Data Mining with Linear Regression Using Genetic Algorithm”, Journal of Advanced Research in Dynamical and Control Systems, vol. 9, no. 02, pp. 1059-1067, 2017.