A Conceptual Framework of Bacterial Foraging Optimization Algorithm for Data Classification

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.

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Abstract

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.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: bacteria foraging optimization algorithm, data classification, k-nearest neighbor, prototype selection, research, Universiti Malaysia Sarawak, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education
Subjects: T Technology > T Technology (General)
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Karen Kornalius
Date Deposited: 06 Mar 2017 08:05
Last Modified: 06 Mar 2017 08:05
URI: http://ir.unimas.my/id/eprint/15508

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