지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국자료분석학회 Journal of The Korean Data Analysis Society Journal of The Korean Data Analysis Society 제6권 제6호
- 발행연도
- 2004.1
- 수록면
- 1,479 - 1,488 (10page)
이용수
초록· 키워드
오류제보하기
Among the data mining techniques, model building for regression should be based on the regression diagnostics such as selection of influent variables or observations. But the existing regression method is not practical for the huge data set. In this paper, a new regression diagnostic method for detecting influential observations which is useful for huge data sets is proposed. The proposed method is compared to the existing diagnostic method through simulations.
목차
등록된 정보가 없습니다.
참고문헌 (11)
참고문헌 신청
Cook,R.D / 1977 / Detection of Influential Observations in Linear regression 19 : 15 ~ 18
David / 1980 / identifying influential Data and sources of collinearity regression diag (stics)
Fayyad U. M / 1996 / Advances in knowledge discovery and data mining
Hampel / 1986 / The approach based on influence function
Kim D / 2004 / Robust Least Squares Support Vector Machine 6 : 943 ~ 951
David / 1980 / identifying influential Data and sources of collinearity regression diag (stics)
Fayyad U. M / 1996 / Advances in knowledge discovery and data mining
Hampel / 1986 / The approach based on influence function
Kim D / 2004 / Robust Least Squares Support Vector Machine 6 : 943 ~ 951
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