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Reseach Article

Analysis of Feature Selection Techniques: A Data Mining Approach

Published on September 2016 by Sheena, Krishan Kumar, Gulshan Kumar
International Conference on Advances in Emerging Technology
Foundation of Computer Science USA
ICAET2016 - Number 1
September 2016
Authors: Sheena, Krishan Kumar, Gulshan Kumar
04fe2120-d39a-4821-b054-3b9eed0c3faf

Sheena, Krishan Kumar, Gulshan Kumar . Analysis of Feature Selection Techniques: A Data Mining Approach. International Conference on Advances in Emerging Technology. ICAET2016, 1 (September 2016), 17-21.

@article{
author = { Sheena, Krishan Kumar, Gulshan Kumar },
title = { Analysis of Feature Selection Techniques: A Data Mining Approach },
journal = { International Conference on Advances in Emerging Technology },
issue_date = { September 2016 },
volume = { ICAET2016 },
number = { 1 },
month = { September },
year = { 2016 },
issn = 0975-8887,
pages = { 17-21 },
numpages = 5,
url = { /proceedings/icaet2016/number1/25879-t024/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Advances in Emerging Technology
%A Sheena
%A Krishan Kumar
%A Gulshan Kumar
%T Analysis of Feature Selection Techniques: A Data Mining Approach
%J International Conference on Advances in Emerging Technology
%@ 0975-8887
%V ICAET2016
%N 1
%P 17-21
%D 2016
%I International Journal of Computer Applications
Abstract

Feature Selection plays the very important role in Intrusion Detection System. One of the major challenge these days is dealing with large amount of data extracted from the network that needs to be analyzed. Feature Selection helps in selecting the minimum number of features from the number of features that need more computation time, large space, etc. This paper, analyzed different feature selection technique on the NSL-KDD dataset by using C45 classifier, compared these techniques by various performance metrics like classifier accuracy, number of features selected, a list of features selected, elapsed time.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Intrusion Detection System Feature Selection Nsl-kdd Data Mining Classification.