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Concurrency and Computation - 2025 - Etcil - Breast Cancer Detection Using A New Parallel Hybrid Logistic Regression Model by vutuyen2rd is a document available to read on EtoBox.
This research article presents a new classifier, CSA-PSO-LR, which combines the Clonal Selection Algorithm and Particle Swarm Optimization to enhance logistic regression for breast cancer diagnosis. The proposed method achieves high accuracy rates of 98.75% on the WDBC dataset and 97.94% on the WBCD dataset, significantly improving upon existing machine learning techniques. The study emphasizes the importance of hyperparameter optimization and CPU parallelization in reducing training time and enhancing mode
- Author
- vutuyen2rd
- Language
- EN