Breast Cancer Classification Using Artificial Neural Network and Feature Selection

Abstract

Breast cancer is still one of the leading causes of death in the world. Prevention can be done if the cancer can be recognized early on whether the cancer is malignant or benign. In this study, a comparison of malignant and benign cancer classifications was performed using two artificial neural network methods, which are the Feed-Forward Backpropagation method and the Elman Recurrent Neural Network method, before and after the feature selection of the data. The result of the study produced that Feed-Forward Backpropagation method using 2 hidden layers is better after the feature selection was performed on the data with an accuracy value of 99,26%.