유방암 재발의 위험인자 예측을 위한 J48과 REPTree의 실험

• 영문명: Experiments of J48 and REPTree for Prediction of Recurrence Risk Factors of Breast Cancer
• 발행기관: 한국IT마케팅학회
• 저자명: 유정희(Jung Hee Yu) 정용규(Yong Gyu Jung)
• 간행물 정보: 『한국IT마케팅학회 논문집』한국IT마케팅학회 논문집 1권 1호, 72~73쪽, 전체 2쪽
• 주제분류: 경제경영 > 경영학
• 파일형태: PDF
• 발행일자: 2014.11.27

영문 초록

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.

목차

Abstract

Ⅰ. 서론

Ⅱ. 관련연구

Ⅲ. 모의실험

Ⅳ. 결론

참고문헌

키워드

Data Mining Maching Learning Decision tree J48 REPTree