Prediction of Breast Cancer using Decision tree and Random Forest Algorithm - Sridevi, N; Anitha, S (International Journal of Computer Sciences and Engineering, 2025)
Breast cancer is one of the most leading causes of death among women. The early detection of anomalies in breast enables the doctor’s in diagnosing the breast cancer easily which can save numerous of lives. In this work, Wisconsin Diagnosis Breast Cancer database is used for experiments in order to predict the breast cancer either benign or malignant. Supervised Machine Learning algorithms namely Decision tree and Random Forests are used to classify the breast cancer. R programming language is used to classify the breast cancer. The performances of the algorithms are measured in terms of accuracy, specificity and sensitivity. The functionality of the algorithms are analysed and the results were discussed.