Breast cancer is one of the leading causes of death among women all around the world. Therefore, true and early diagnosis of breast cancer is an important problem. The Lagrange interpolation was used in this study for the diagnosis of breast cancer. The Wisconsin Breast Cancer dataset (WBCD), derived from the University of California Irvine machine learning database, was used for the purpose of testing the proposed method was determined as 98%. In this method, we are looking for two equations by Lagrange interpolation because of two classes that are exist in breast cancer data set. We receive each sample and it will define rate of vicinity it's to each class (malignant or benign). So, the class of mentioned sample will be recognized. Moreover, the most appropriate attributes for the diagnosis of breast cancer were determined from the WBCD in this study. It is considered that the proposed method will be useful in similar medical practices.
Breast cancer, Lagrange interpolation, extreme learning machine, expert system
