RISS 학술연구정보서비스

검색
다국어 입력

http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.

변환된 중국어를 복사하여 사용하시면 됩니다.

예시)
  • 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
  • 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
닫기
    인기검색어 순위 펼치기

    RISS 인기검색어

      검색결과 좁혀 보기

      선택해제

      오늘 본 자료

      • 오늘 본 자료가 없습니다.
      더보기
      • 무료
      • 기관 내 무료
      • 유료
      • KCI등재후보

        의사결정나무와 로지스틱 회귀분석을 이용한 태권도 수련생 이탈 예측을 위한 비교 연구

        권태원(Kwon Tae-Won),구유희(Koo Yu-Hoe) 한국체육과학회 2008 한국체육과학회지 Vol.17 No.2

        The purpose of this study is to suggest the most appropriate prediction model for prediction of secession of trainees of Taekwondo gymnasium through decision-making tree technique among logistics regression analysis and data mining techniques. In order to accomplish the purpose of this study, I have distributed 1,500 questionnaires sheets to the trainees using by convenience sampling method among non probability sampling extraction methods by setting trainees of Taekwondo gymnasium located in Gyeonggi-Do and Incheon Results of this study derived from this procedure and method are as follows. 1. As the result of examining the difference of level of specialty between decision-making tree technique & logistics regression analysis, in the level of specialty predicting carry forward number of people with actual number of carry-over, logistics regression analysis was 92.9% and decision-making tree technique showed a little higher at 96.3%. 2. As the result of examining the difference of level of sensitivity between decision-making tree technique & logistics regression analysis, in the level of sensitivity predicting carry forward number of people with actual number of carry-over, logistics regression analysis was 64.0% and decision-making tree technique showed 44.5%. 3. As the result of examining the difference of level of accuracy between decision-making tree technique & logistics regression analysis, in the level of accuracy predicting carry forward number of people with actual number of carry-over, logistics regression analysis was 86.8% and logistics regression analysis showed 87.6%. 4. As the results of examining variables affecting secession of trainees of Taekwondo gymnasium between decision-making tree technique and logistics regression analysis, in case of decision-making tree technique, variables were training period, grade, satisfaction for instructor, recommendation will, and satisfaction of facility and in case of logistics regression analysis, variables were training period, grade, recommendation will, satisfaction for instructor, and per sex. Summarizing the above result, as the result of comparison analysis of secession prediction of trainees of Taekwondo gymnasium between decision-making tree technique and logistics regression analysis, the two models showed all high prediction rate in the level of accuracy and there was no difference of prediction rate between the two analysis models. This result is believed to be because the same variables affecting secession were used in the same.

      연관 검색어 추천

      이 검색어로 많이 본 자료

      활용도 높은 자료

      해외이동버튼