A new multiobjective Harris Hawk Optimization algorithm for the diagnosis of breast cancer

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A new multiobjective Harris Hawk Optimization algorithm for the diagnosis of breast cancer

A new multiobjective Harris Hawk Optimization algorithm for the diagnosis of breast cancer

Authors : Alara Sermutlu, Tansel Dökeroğlu

Pages : 17-25

View : 32 | Download : 40

Publication Date : 2025-07-31

Article Type : Research Paper

Abstract :Breast cancer, a highly prevalent and life-threatening disease, affects millions of individuals worldwide, particularly women. Feature-based methods are widely employed for early diagnosis of breast cancer, and selecting the optimal feature set remains a significant and challenging problem. In this study, we introduce a novel Multi-objective Harris Hawk Optimization algorithm, which integrates an adaptive K-Nearest Neighbor classifier. Comprehensive experiments were conducted on two well-known datasets. The proposed approach achieves 31-45% reductions in the total number of selected features across all datasets, significantly lowering computational costs and improving the accuracy of diagnostics up to 95-97%.
Keywords : meme kanseri, Harris Şahini, meta-sezgizel, K-En Yakın Komşu

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