Breast Cancer classification using Neural networks

Nowadays, due to lack of awareness of breast cancer and its signs that show, as well as methods for prevention, causes them to be one of the most deadly types of cancer and the death rate has significantly increased. Hence, in order to stop the spread of cancer, early identification at a nearly stage is critical as well as important. Breast cancer is further classified in to two types, malignant and benign. This study used machine learning techniques and neural network methods to classify the breast cancer types. A system is automated to carry out its opinion that is also automated, for breast cancer. This approach uses DNN (deep neural network), CNN (Convolutional Neural Network) and ANN Artificial Neural Network) and RFE (recursive feature elimination) for feature selection. DNN is applied with a multitude of layers of functions processing is applied to categorize the breast cancer data set. The result shows DNN is comparatively more outperforming with an accuracy of 97%.