데이터 마이닝 기법을 이용한 전공이탈자 예측 모형에 관한 연구
A Study on Predicting Model of Students Leaving Their Majors Using Data Mining Technique
- 주제(키워드) 데이터마이닝 , 의사결정나무 , SAS E-Miner , Lift Chart , ROC Chart , 이익도표 , Data Mining , Predicting Model , Major Separation Rate
- 발행기관 江陵大學校 大學院
- 지도교수 임영문
- 발행년도 2007
- 학위수여년월 2007. 2
- 학위명 석사
- 학과 및 전공 産業工學科
- 원문페이지 v, 50 p.
- 본문언어 한국어
초록/요약
Nowadays most colleges are confronting with a serious problem because many students have left their majors at the colleges. In order to make a countermeasure for reducing major separation rate, many universities are trying to find a proper solution. As a similar endeavor, the objective of this paper is to find a predicting model of students leaving their majors. The sample for this study was chosen from a university in Kangwon-Do during seven years (2000.3.1 ～ 2006. 6.30). In this study, the ratio of training sample versus testing sample among partition data was controlled as 50% : 50% for a validation test of data division. Also, this study provides values about accuracy, sensitivity, specificity about three kinds of algorithms including CHAID, CART and C4.5. According to the analysis result, CART showed the best performance for classification of students leaving their majors. In addition, ROC chart and gains chart were used for classification of students leaving their majors. The analysis results were very informative since those enable us to know the most important factors such as semester taking a course, grade on cultural subjects, scholarship, grade on majors, and total completion of courses which can affect students leaving their majors.
more목차
1. 서론 = 1
1.1 연구 동기 및 목적 = 1
1.2 선행연구 = 2
1.3 연구방법 = 2
2. 데이터마이닝 = 3
2.1 데이터마이닝의 개요 = 3
2.2 데이터마이닝의 발전배경 = 3
2.3 데이터마이닝 수행과정 = 5
2.4 데이터마이닝 역할 및 기법 = 6
3. 의사결정나무 = 8
3.1 의사결정나무 개요 및 구성요소 = 8
3.2 의사결정나무의 형성 = 8
3.3 의사결정나무 알고리즘 = 9
4. 데이터 셋 = 22
5. 연구 결과 및 분석 = 28
5.1 SAS Enterprise Miner를 이용한 데이터 분석 = 28
5.2 알고리즘 비교 분석 = 29
5.3 최적예측모형 = 34
6. 결론 및 추후연구사항 = 39
참고문헌 = 41
[ 별첨 ] = 43
