- Twostep Clustering of Environmental Indicator Survey Data
- Twostep Clustering of Environmental Indicator Survey Data
- ㆍ 저자명
- Park. Hee-Chang
- ㆍ 간행물명
- 한국데이터정보과학회지
- ㆍ 권/호정보
- 2006년|17권 1호|pp.1-11 (11 pages)
- ㆍ 발행정보
- 한국데이터정보과학회
- ㆍ 파일정보
- 정기간행물|ENG| PDF텍스트
- ㆍ 주제분야
- 기타
Data mining technique is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are decision tree, association rules, clustering, neural network and so on. Clustering is the process of grouping the data into clusters so that objects within a cluster have high similarity in comparison to one another. It has been widely used in many applications, such that pattern analysis or recognition, data analysis, image processing, market research on off-line or on-line and so on. We analyze Gyeongnam social indicator survey data by 2001 using twostep clustering technique for environment information. The twostep clustering is classified as a partitional clustering method. We can apply these twostep clustering outputs to environmental preservation and improvement.