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The Use of Output Combiners in Enhancing the Performance of Large Data for ANNs

Deriving classification information from large databases presents several challenges. The current methods used to classify a large dataset have the disadvantage of requiring long computational time and high complexity. In addition, most of the methods can only deal with selected features of the data...

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Main Authors: Mumtazimah, Mohamad, Md Yazid, Mohd Saman, Muhammad Suzuri, Hitam
Format: Article
Language:English
Published: 2014
Subjects:
QA Mathematics
Online Access:http://eprints.unisza.edu.my/4838/1/FH02-FIK-14-00846.jpg
http://eprints.unisza.edu.my/4838/
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spelling my-unisza-ir.48382022-09-13T05:43:04Z http://eprints.unisza.edu.my/4838/ The Use of Output Combiners in Enhancing the Performance of Large Data for ANNs Mumtazimah, Mohamad Md Yazid, Mohd Saman Muhammad Suzuri, Hitam QA Mathematics Deriving classification information from large databases presents several challenges. The current methods used to classify a large dataset have the disadvantage of requiring long computational time and high complexity. In addition, most of the methods can only deal with selected features of the data while some of the methods can only deal with categorical or numerical attributes. This paper proposes large data solutions by defining the strategy to classify large data with local processors of Artificial Neural Networks (ANNs). A combination technique for reordered ANNs is proposed in modeling the combination of multiple ANNs as part of framework approach. Several repeated experiments with different techniques tested with the MNIST dataset show good percentage of performance and reduction of errors. The results obtained are in line with the importance of good performance achieved with the use of combiner for a large data solution. 2014-02 Article PeerReviewed image en http://eprints.unisza.edu.my/4838/1/FH02-FIK-14-00846.jpg Mumtazimah, Mohamad and Md Yazid, Mohd Saman and Muhammad Suzuri, Hitam (2014) The Use of Output Combiners in Enhancing the Performance of Large Data for ANNs. IAENG International Journal of Computer Science, 41 (1). pp. 38-47. ISSN 1819-656X
institution Universiti Sultan Zainal Abidin
building UNISZA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Sultan Zainal Abidin
content_source UNISZA Institutional Repository
url_provider https://eprints.unisza.edu.my/
language English
topic QA Mathematics
spellingShingle QA Mathematics
Mumtazimah, Mohamad
Md Yazid, Mohd Saman
Muhammad Suzuri, Hitam
The Use of Output Combiners in Enhancing the Performance of Large Data for ANNs
description Deriving classification information from large databases presents several challenges. The current methods used to classify a large dataset have the disadvantage of requiring long computational time and high complexity. In addition, most of the methods can only deal with selected features of the data while some of the methods can only deal with categorical or numerical attributes. This paper proposes large data solutions by defining the strategy to classify large data with local processors of Artificial Neural Networks (ANNs). A combination technique for reordered ANNs is proposed in modeling the combination of multiple ANNs as part of framework approach. Several repeated experiments with different techniques tested with the MNIST dataset show good percentage of performance and reduction of errors. The results obtained are in line with the importance of good performance achieved with the use of combiner for a large data solution.
format Article
author Mumtazimah, Mohamad
Md Yazid, Mohd Saman
Muhammad Suzuri, Hitam
author_facet Mumtazimah, Mohamad
Md Yazid, Mohd Saman
Muhammad Suzuri, Hitam
author_sort Mumtazimah, Mohamad
title The Use of Output Combiners in Enhancing the Performance of Large Data for ANNs
title_short The Use of Output Combiners in Enhancing the Performance of Large Data for ANNs
title_full The Use of Output Combiners in Enhancing the Performance of Large Data for ANNs
title_fullStr The Use of Output Combiners in Enhancing the Performance of Large Data for ANNs
title_full_unstemmed The Use of Output Combiners in Enhancing the Performance of Large Data for ANNs
title_sort use of output combiners in enhancing the performance of large data for anns
publishDate 2014
url http://eprints.unisza.edu.my/4838/1/FH02-FIK-14-00846.jpg
http://eprints.unisza.edu.my/4838/
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score 13.239859

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