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Binary Bitwise Artificial Bee Colony as Feature Selection Optimization Approach within Taguchi's T-Method

Harudin, Nolia and Ramlie, Faizir and Wan Muhamad, Wan Zuki Azman and Muhtazaruddin, M. N. and Jamaludin, Khairur Rijal and Abu, Mohd. Yazid and Marlan, Zulkifli Marlah (2021) Binary Bitwise Artificial Bee Colony as Feature Selection Optimization Approach within Taguchi's T-Method. Mathematical Problems in Engineering, 2021 . p. 5592132. ISSN 1024-123X

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Official URL: http://dx.doi.org/10.1155/2021/5592132


Taguchi's T-Method is one of the Mahalanobis Taguchi System-(MTS-) ruled prediction techniques that has been established specifically but not limited to small, multivariate sample data. The prediction model's complexity aspect can be further enhanced by removing features that do not provide valuable information on the overall prediction. In order to accomplish this, a matrix called orthogonal array (OA) is used within the existing Taguchi's T-Method. However, OA's fixed-scheme matrix and its drawback in coping with the high-dimensionality factor led to a suboptimal solution. On the contrary, the usage of SNR (dB) as its objective function was a reliable measure. The application of Binary Bitwise Artificial Bee Colony (BitABC) has been adopted as the novel search engine that helps cater to OA's limitation within Taguchi's T-Method. The generalization aspect using bootstrap was a fundamental addition incorporated in this research to control the effect of overfitting in the analysis. The adoption of BitABC has been tested on eight (8) case studies, including large and small sample datasets. The result shows improved predictive accuracy ranging between 13.99% and 32.86% depending on cases. This study proved that incorporating BitABC techniques into Taguchi's T-Method methodology effectively improved its prediction accuracy.

Item Type:Article
Uncontrolled Keywords:Taguchi's T-Method, BitABC
Subjects:T Technology > T Technology (General)
Divisions:Razak School of Engineering and Advanced Technology
ID Code:95290
Deposited By: Widya Wahid
Deposited On:30 Apr 2022 06:26
Last Modified:30 Apr 2022 06:26

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