Binary Grey Wolf Optimizer with K-Nearest Neighbor classifier for Feature Selection

Iteration number and population size are two key factors that influence the effectiveness of a certain feature selection algorithm. Randomly choosing these factors, however, might be an impractical approach that could lead to low algorithm accuracy. In this paper, we assessed the changes in the accu...

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Main Authors: Al-Wajih, R., Abdulakaddir, S.J., Aziz, N.B.A., Al-Tashi, Q.
Format: Conference or Workshop Item
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.29891 /
Published: Institute of Electrical and Electronics Engineers Inc. 2020
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097552219&doi=10.1109%2fICCI51257.2020.9247792&partnerID=40&md5=9399b4c26698006e1581b88d8f72ab1f
http://eprints.utp.edu.my/29891/
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spelling utp-eprints.298912022-03-25T03:05:32Z Binary Grey Wolf Optimizer with K-Nearest Neighbor classifier for Feature Selection Al-Wajih, R. Abdulakaddir, S.J. Aziz, N.B.A. Al-Tashi, Q. Iteration number and population size are two key factors that influence the effectiveness of a certain feature selection algorithm. Randomly choosing these factors, however, might be an impractical approach that could lead to low algorithm accuracy. In this paper, we assessed the changes in the accuracy of Binary Grey Wolf Optimizer (BGWO) at varying a function of iteration number (50,100,150 and 200) and population size (10,20,30) in four benchmark datasets. The results generally indicate that there is an optimum iteration number (T) beyond which the accuracy of BGWO started to decrease. Similarly, it was seen that an optimum population size (N) exists, which yield a high average accuracy of the BGWO algorithm. The findings suggest that it is essential to optimize the iteration number and population size before the execution of BGWO. © 2020 IEEE. Institute of Electrical and Electronics Engineers Inc. 2020 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097552219&doi=10.1109%2fICCI51257.2020.9247792&partnerID=40&md5=9399b4c26698006e1581b88d8f72ab1f Al-Wajih, R. and Abdulakaddir, S.J. and Aziz, N.B.A. and Al-Tashi, Q. (2020) Binary Grey Wolf Optimizer with K-Nearest Neighbor classifier for Feature Selection. In: UNSPECIFIED. http://eprints.utp.edu.my/29891/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Iteration number and population size are two key factors that influence the effectiveness of a certain feature selection algorithm. Randomly choosing these factors, however, might be an impractical approach that could lead to low algorithm accuracy. In this paper, we assessed the changes in the accuracy of Binary Grey Wolf Optimizer (BGWO) at varying a function of iteration number (50,100,150 and 200) and population size (10,20,30) in four benchmark datasets. The results generally indicate that there is an optimum iteration number (T) beyond which the accuracy of BGWO started to decrease. Similarly, it was seen that an optimum population size (N) exists, which yield a high average accuracy of the BGWO algorithm. The findings suggest that it is essential to optimize the iteration number and population size before the execution of BGWO. © 2020 IEEE.
format Conference or Workshop Item
author Al-Wajih, R.
Abdulakaddir, S.J.
Aziz, N.B.A.
Al-Tashi, Q.
spellingShingle Al-Wajih, R.
Abdulakaddir, S.J.
Aziz, N.B.A.
Al-Tashi, Q.
Binary Grey Wolf Optimizer with K-Nearest Neighbor classifier for Feature Selection
author_sort Al-Wajih, R.
title Binary Grey Wolf Optimizer with K-Nearest Neighbor classifier for Feature Selection
title_short Binary Grey Wolf Optimizer with K-Nearest Neighbor classifier for Feature Selection
title_full Binary Grey Wolf Optimizer with K-Nearest Neighbor classifier for Feature Selection
title_fullStr Binary Grey Wolf Optimizer with K-Nearest Neighbor classifier for Feature Selection
title_full_unstemmed Binary Grey Wolf Optimizer with K-Nearest Neighbor classifier for Feature Selection
title_sort binary grey wolf optimizer with k-nearest neighbor classifier for feature selection
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2020
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097552219&doi=10.1109%2fICCI51257.2020.9247792&partnerID=40&md5=9399b4c26698006e1581b88d8f72ab1f
http://eprints.utp.edu.my/29891/
_version_ 1741197315634364416
score 11.62408

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