Optimising Machine Learning for Breast Cancer Diagnosis

Created using ChatSlide

This presentation explores the application of machine learning in medical diagnostics, focusing on breast cancer prediction using the Wisconsin Breast Cancer Dataset. It examines algorithm performance through preprocessing, feature scaling, and hyperparameter optimisation, comparing Logistic Regression and Decision Tree models. Analyses reveal key performance metrics, bias-variance trade-offs, and the reliability of Logistic Regression. Limitations and opportunities for future advancements...