Brief review of classification algorithm on breast cancer

Abstract

Breast cancer is a malignant neoplasm disease which is an abnormal growth of breast tissue that is different from surrounding tissue. It became the second most case of death that caused by cancer after lung cancer. Several studies have been done to diagnose patients of breast cancer using various type of algorithm. This paper presents a brief review of breast cancer detection using datamining classification algorithm. C4.5, Naive Bayes and K-Nearest Neighbour algorithm are applied on breast cancer data set. Outputs are decision tree, models and computations. This study aims to evaluate performance of those three-data mining classification algorithm.