Zainor Ridzuan Yahya
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Preferred name
Zainor Ridzuan Yahya
Official Name
Zainor Ridzuan, Yahya
Alternative Name
Yahya, Zainor Ridzuan
Yahya, Z. R.
Ridzuan Yahya, Zainor
Main Affiliation
Scopus Author ID
50862369800
Researcher ID
GNH-4483-2022

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  • Publication
    Hybrid Mahalanobis Taguchi System with Binary Whale Optimisation Feature Selection for the Wisconsin Breast Cancer Dataset
    (Semarak Ilmu Publishing, 2023)
    Chow Yong Huan
    ;
    Wan Zuki Azman Wan Muhamad
    ;
    Zainor Ridzuan Yahya
    ;
    Nor Hizamiyani Abdul Azziz
    ;
    Tan Chye Lih
    ;
    Tan Xiao Jian
    The Mahalanobis-Taguchi System (MTS) is a statistical approach used in breast cancer research to facilitate early detection and promote efficient treatment. The technique analyses mammogram images for significant features using a multivariate statistical analysis technique. It combines the Mahalanobis distance (MD) and Taguchi's method to determine the differences between benign and malignant samples. While orthogonal array (OA) has been widely used in MTS, it has been criticised for providing suboptimal results due to insufficient coverage of feature combinations during the feature optimisation process. To address this issue, the Binary Whale Optimisation Algorithm (BWOA) is proposed as an improved search algorithm for MTS. This paper aims to develop a novel hybrid method that enhances the efficiency of the Mahalanobis Taguchi System (MTS). The performance of feature selection ability due to different MTS hybrid algorithms were also compared. BWOA simulates the hunting behaviour of humpback whales and works by exploring new regions of the solution space, gradually narrowing the search space, and fine-tuning the solution. MTS-BWOA demonstrated its enhanced capability in feature optimisation compared to traditional MTS methods and has the potential to be applied in other medical imaging domains.
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