유방암 재발의 위험인자 예측을 위한 J48과 REPTree의 실험

Experiments of J48 and REPTree for Prediction of Recurrence Risk Factors of Breast Cancer

Cancer prevalence number to live with cancer in 1.1 million people currently , is a type of malignant tumor that occurs most easily in women , breast cancer of which the disease in the uterus following , threaten women's health in women can be . The exact cause of breast cancer is not yet known , but if you are experienced carbide in early mechanical , single woman and the woman who has never conceived a child , a woman gave birth to a baby the first 30 after age , breast milk frequency from women in is not raised appears highly associated with the female hormones are presented , but the exact mechanism is unclear situation . However , we note, breast cancer is that it is a cancer likelihood of recurrence rate is also about 22% higher . In this paper , I want to compare the classification performance of REPTree and J48 in the ML algorithm which has data for the likelihood of recurrence of breast cancer . Through the performance comparison, to ensure that any algorithm provides more accurate classification, as a result, the goal of this study is to find a more accurate prediction algorithms.