Breast Cancer Classification using Decision Tree Algorithms

Cancer is a major health issue that affects individuals all over the world. This disease has claimed lives of many people, and will continue to do so in future. Breast cancer recently surpassed cervical as most frequent among women both industrialized developing countries it now second leading cause mortality women. A high number die each year result this disease. significantly easier treat if caught early. paper introduces decision tree-based data mining technique for breast early detection with highest accuracy, which helps patients recover. cancers are classed benign (unable penetrate surrounding tissue) or malignant (able infiltrate adjacent growths. Two tests were included review. The primary study uses 10 samples from Kaggle archive, whereas follow-up 286 same pool. Decision Tree's accuracy first trial was 100%, while 97.9% inquiry. These findings justify use proposed machine learning-based Tree classifier pre-evaluating triage decision-making prior availability data.