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초록
In classification and discrimination, we often face with incomplete group variable arising typically from many missing values and/or incredible cases. This paper suggests the use of K-means clustering for pre-adjusting incompleteness and in turn classification based on generalized statistical distance is performed. For illustrating the proposed procedure, simulation study is conducted comparatively with CART in data mining and traditional techniques which are ignoring incompleteness of group variable. Simulation study manifests that our methodology out-performs.
키워드
CART; Classification; Incomplete variable; K-means clustering; CART; Classification; Incomplete variable; K-means clustering
- 제목
- Pre-adjustment of incomplete group variable via K-means clustering
- 저자
- 황선영; 한혜은
- 발행일
- 2004-09
- 저널명
- 한국데이터정보과학회지
- 권
- 15
- 호
- 3
- 페이지
- 555 ~ 563