Machine Learning Based Mammogram Classification from Mnist

Abstract

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 were 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 analysed where Neural Network approach provides more ‘accuracy’ and ‘precision’ as compared to Support Vector Machine in the classification of breast cancer, ANN seems to be fast and efficient method. In our project we have used the following algorithms Support Vector Machine (SVM) as existing and Artificial Neural Network (ANN) as proposed system compared in terms of accuracy