Breast Cancer Prediction Using Logistic Regression

Abstract: In this paper, we research the early detection of breast cancer. We use a machine learning approach. We use the Breast Cancer Wisconsin Diagnostic dataset (WBCD). The major focus is on the predictive model of logistic regression. Firstly, we check performance metrics: accuracy, precision-recall, and F1 score. We achieved a good accuracy, which helps to prove the model is acceptable, as it is simple and interpretable. The results show that logistic regression is an effective method for detecting cancers, making it a promising choice for breast cancer diagnosis. The study also examines possible future developments by investigating several machine learning models to further boost detection rates and forecasting power