The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Metadata Harvesting (OAI2)
  • Digital Archiving Policy

IJACSA

  • About the Journal
  • Call for Papers
  • Author Guidelines
  • Fees/ APC
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving
  • Editorial Board

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors

Computing Conference 2021

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys) 2021

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC) 2021

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future of Information and Communication Conference (FICC) 2021

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Guidelines
  • Fees
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Subscribe

Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

A Feature Selection Algorithm based on Mutual Information using Local Non-uniformity Correction Estimator

Author 1: Ahmed I. Sharaf
Author 2: Mohamed Abu El-Soud
Author 3: Ibrahim El-Henawy

Download PDF

Digital Object Identifier (DOI) : 10.14569/IJACSA.2017.080656

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 6, 2017.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Feature subset selection is an effective approach used to select a compact subset of features from the original set. This approach is used to remove irrelevant and redundant features from datasets. In this paper, a novel algorithm is proposed to select the best subset of features based on mutual information and local non-uniformity correction estimator. The proposed algorithm consists of three phases: in the first phase, a ranking function is used to measure the dependency and relevance among features. In the second phase, candidates with higher dependency and minimum redundancy are selected to participate in the optimal subset. In the last phase, the produced subset is refined using forward and backward wrapper filter to ensure its effectiveness. A UCI machine repository datasets are used for validation and testing. The performance of the proposed algorithm has been found very significant in terms of classification accuracy and time complexity.

Keywords: Feature subset selection; irrelevant features; mutual information; local non-uniformity correction

Ahmed I. Sharaf, Mohamed Abu El-Soud and Ibrahim El-Henawy, “A Feature Selection Algorithm based on Mutual Information using Local Non-uniformity Correction Estimator” International Journal of Advanced Computer Science and Applications(IJACSA), 8(6), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080656

@article{Sharaf2017,
title = {A Feature Selection Algorithm based on Mutual Information using Local Non-uniformity Correction Estimator},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080656},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080656},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {6},
author = {Ahmed I. Sharaf and Mohamed Abu El-Soud and Ibrahim El-Henawy}
}


IJACSA

Upcoming Conferences

Future of Information and Communication Conference (FICC) 2021

29-30 April 2021

  • Virtual

Computing Conference 2021

15-16 July 2021

  • London, United Kingdom

IntelliSys 2021

2-3 September 2021

  • Amsterdam, The Netherlands

Future Technologies Conference (FTC) 2021

28-29 October 2021

  • Vancouver, Canada
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© 2018 The Science and Information (SAI) Organization Limited. Registered in England and Wales. Company Number 8933205. All rights reserved. thesai.org