AN EFFICIENT NEURAL NETWORK BASED APPROACH FOR THE DETECTION OF BREAST CANCER
Women’s of young age of the developing nations are suffering from breast cancer which is considered as the major cause of deaths and it is increasing with a rapid rate, to get control over this early detection and diagnosis of this disease is highly required. In order to implement this various machine learning techniques are becoming popular now a days especially the neural networks because of their capacity to handle the enormous data of various complex datasets and to perform various computation for providing better results with minimal rate of error. In this work we have used two types of neural networks MLP and RNN over Diagnostic dataset of Breast Cancer. Model of both the networks were tuned using various hyper parameters in order to get precise and accurate results.