A Conceptual Framework of Bacterial Foraging Optimization Algorithm for Data Classification

Most previous works on Bacterial Foraging Optimization Algorithm (BFOA) for data classification were integrated BFOA as a feature selection algorithm and parameters optimizer for other classifiers. To the best of our knowledge, no effort has been carried out to fully utilize BFOA as a classifier....

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Main Authors: Hossin, M., Mohd Suria, F.
Format: Proceeding
Language:English
English
Published: 2016
Subjects:
Online Access:http://ir.unimas.my/id/eprint/15508/
http://ir.unimas.my/id/eprint/15508/1/PROCSIT2016%20-%20A%20Conceptual%20Framework%20of%20Bacterial%20Foraging%20Optimization%20Algorithm%20for%20Data%20Classification%20%28abstract%29.pdf
http://ir.unimas.my/id/eprint/15508/2/PROCSIT%202016%20-%20Ptogramme%20Book.pdf
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author Hossin, M.
Mohd Suria, F.
author_facet Hossin, M.
Mohd Suria, F.
author_sort Hossin, M.
building UNIMAS Institutional Repository
collection Online Access
description Most previous works on Bacterial Foraging Optimization Algorithm (BFOA) for data classification were integrated BFOA as a feature selection algorithm and parameters optimizer for other classifiers. To the best of our knowledge, no effort has been carried out to fully utilize BFOA as a classifier. This paper presents a conceptual framework of instance-based BFOA. The proposed conceptual framework is designed based on the prototype searching approach whose target is to obtain an optimal reference set (cardinality) and simultaneously aim for high generalization performance by utilizing the strengths of BFOA.
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institution Universiti Malaysia Sarawak
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language English
English
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publishDate 2016
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spelling unimas-155082017-03-06T08:05:39Z http://ir.unimas.my/id/eprint/15508/ A Conceptual Framework of Bacterial Foraging Optimization Algorithm for Data Classification Hossin, M. Mohd Suria, F. T Technology (General) Most previous works on Bacterial Foraging Optimization Algorithm (BFOA) for data classification were integrated BFOA as a feature selection algorithm and parameters optimizer for other classifiers. To the best of our knowledge, no effort has been carried out to fully utilize BFOA as a classifier. This paper presents a conceptual framework of instance-based BFOA. The proposed conceptual framework is designed based on the prototype searching approach whose target is to obtain an optimal reference set (cardinality) and simultaneously aim for high generalization performance by utilizing the strengths of BFOA. 2016 Proceeding NonPeerReviewed text en http://ir.unimas.my/id/eprint/15508/1/PROCSIT2016%20-%20A%20Conceptual%20Framework%20of%20Bacterial%20Foraging%20Optimization%20Algorithm%20for%20Data%20Classification%20%28abstract%29.pdf text en http://ir.unimas.my/id/eprint/15508/2/PROCSIT%202016%20-%20Ptogramme%20Book.pdf Hossin, M. and Mohd Suria, F. (2016) A Conceptual Framework of Bacterial Foraging Optimization Algorithm for Data Classification. In: Progress in Computer Sciences and Information Technology International Conference (PROCSIT'l6), 20 - 22 December 2016, Langkawi Island, Malaysia.
spellingShingle T Technology (General)
Hossin, M.
Mohd Suria, F.
A Conceptual Framework of Bacterial Foraging Optimization Algorithm for Data Classification
title A Conceptual Framework of Bacterial Foraging Optimization Algorithm for Data Classification
title_full A Conceptual Framework of Bacterial Foraging Optimization Algorithm for Data Classification
title_fullStr A Conceptual Framework of Bacterial Foraging Optimization Algorithm for Data Classification
title_full_unstemmed A Conceptual Framework of Bacterial Foraging Optimization Algorithm for Data Classification
title_short A Conceptual Framework of Bacterial Foraging Optimization Algorithm for Data Classification
title_sort conceptual framework of bacterial foraging optimization algorithm for data classification
topic T Technology (General)
url http://ir.unimas.my/id/eprint/15508/
http://ir.unimas.my/id/eprint/15508/1/PROCSIT2016%20-%20A%20Conceptual%20Framework%20of%20Bacterial%20Foraging%20Optimization%20Algorithm%20for%20Data%20Classification%20%28abstract%29.pdf
http://ir.unimas.my/id/eprint/15508/2/PROCSIT%202016%20-%20Ptogramme%20Book.pdf