한국데이터정보과학회:학술대회논문집
- 한국데이터정보과학회 2004년도 추계학술대회
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- Pages.77-86
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- 2004
Environmental Survey Data Modeling using K-means Clustering Techniques
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Park, Hee-Chang
(Department of Statistics, Changwon National University) ;
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Cho, Kwang-Hyun
(Department of Statistics, Changwon National University)
- 발행 : 2004.10.30
초록
Clustering is the process of grouping the data into clusters so that objects within a cluster have high similarity in comparison to one another. In this paper we used k-means clustering of several clustering techniques. The k-means Clustering is classified as a partitional clustering method. We analyze 2002 Gyeongnam social indicator survey data using k-means clustering techniques for environmental information. We can use these outputs given by k-means clustering for environmental preservation and environmental improvement.