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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