최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기응용통계연구 = The Korean journal of applied statistics, v.34 no.6, 2021년, pp.905 - 922
이승훈 (고려대학교 통계학과) , 송주원 (고려대학교 통계학과)
Cluster analysis is one of unsupervised learning techniques used for discovering clusters when there is no prior knowledge of group membership. K-means, one of the commonly used cluster analysis techniques, may fail when the number of variables becomes large. In such high-dimensional cases, it is co...
Arabie P and Hubert L (1994). Cluster analysis in marketing research, Advanced Methods in Marketing Research, 160-189, Oxford: Blackwell.
Choi Y and Baek I (2017). Implication and lesson for city reconstruction experience in the United States, Monthly Housing Finance Report(in korean version), 157, 22-35.
Dempster A, Laird N, and Rubin D (1977). Maximum likelihood from incomplete data via the EM algorithm, Journal of the Royal Statistical Society, Series B (Methodological), 39, 1-38.
De Soete G and Carroll JD (1994). K-means clustering in a low-dimensional euclidean space, New Approaches in Classification and Data Analysis, 212-219, Heidelberg: Springer.
Ding C, He X, Zha H, and Simon HD (2002). Adaptive dimension reduction for Clustering High Dimensional Data, Proc 2nd IEEE Intl Conf Data Mining, 147-154.
Ghahramani Z and Hinton GE (1996). The EM algorithm for mixtures of factor analyzers, Technical Report CRG-TR-96-1, University of Toronto, Canada.
Gilley OW and Pace RK (1996). On the Harrison and Rubinfeld data, Journal of Environmental Economics and Management, 31, 403-405.
Harrison D and Rubinfeld DL (1978). Hedonic prices and the demand for clean air, Journal of Environmental Economics and Management, 5, 81-102.
Milligan GW and Cooper MC (1985). An examination of procedures for determining the number of clusters in a data set, Psychometrika, 50, 159-179.
Rocci R, Gattone SA, and Vichi M (2011). A new dimension reduction method: factor discriminant K-means, Journal of Classification, 28, 210-226.
Roweis S (1998). EM algorithms for PCA and SPCA. Advances in Neural Information Processing Systems, Advances in Neural Information Processing Systems 10 - Proceedings of the 1997 Conference, 626-632, Elsevier.
Lee S (2021). Probabilistic reduced K-means cluster analysis, Master's thesis, Department of Statistics, Korea University, Korea(in korean version).
Timmerman ME, Ceulemans E, De Roover K, and Van Leeuwen K (2013). Subspace K-means clustering, Behavior Research Methods, 45, 1011-1023.
Timmerman ME, Ceulemans E, Kiers HAL, and Vichi M (2010). Factorial and reduced K-means reconsidered, Computational Statistics and Data Analysis, 54, 1858-1871.
Tipping ME and Bishop CM (1999a). Mixtures of probabilistic principal component analyzers, Neural Computation, 11, 443-482.
Tipping ME and Bishop CM (1999b). Probabilistic principal component analysis, Journal of the Royal Statistical Society, Series B (Statistical Methodology), 61, 611-622.
Vichi M and Kiers HAL (2001). Factorial K-means analysis for two-way data, Computational Statistics and Data Analysis, 37, 49-64.
*원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다.
오픈액세스 학술지에 출판된 논문
※ AI-Helper는 부적절한 답변을 할 수 있습니다.