Classification of breast cancer data based on neural network algorithm

Abstract

In today's world, breast cancer has become the most common malignant tumor, so this paper mainly classifies the features of breast cancer through BP neural network to improve the accuracy of research and judgment. This paper mainly adopts 30 breast cancer feature data of 569 cases, and then obtains the feature data used in this BP neural network through correlation analysis, feature selection and principal component analysis. By training, the BP neural network that is most suitable for this data is constructed from aspects such as the number of hidden layers, loss function, and iteration times, ultimately improving the accuracy to 100%.