Breast Cancer Classification using Support Vector Machine and Neural Network

Breast cancer is one of the most leading causes of death among women. The early detection of abnormalities in breast enables the radiologist in diagnosing the breast cancer easily. Efficient tools in diagnosing the cancerous breast will help the medical experts in accurate diagnosis and timely treatment to the patients. In this work, experiments was carried out using Wisconsin Diagnosis Breast Cancer database to classify the breast cancer as either benign or malignant. Supervised learning algorithm -Support Vector Machine (SVM) with kernels like Linear, and Neural Network (NN) are used for comparison to achieve this tasks. The performances of the models are analyzed where Neural Network approach provides more accuracy and precision as compared to Support Vector Machine in the classification of breast cancer, and seems to be fast and efficient method.