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그리드를 기반으로 한 K-평균 알고리즘 개발 원문보기
Grid-based K-Means Algorithm

  • 저자

    이선명

  • 학위수여기관

    昌原大學校 大學院

  • 학위구분

    국내석사

  • 학과

    수학통계학과

  • 지도교수

  • 발행년도

    2003

  • 총페이지

    24p.

  • 키워드

    그리드 K-평균 알고리즘 통계수학;

  • 언어

    kor

  • 원문 URL

    http://www.riss.kr/link?id=T9469047&outLink=K  

  • 초록

    Data mining is the task of discovering interesting patterns from large amounts of data in databases. The method 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 hava high similarity in comparison to one another. In this paper we study k-means method of several clustering techniques. The k-means algorithm is classified as a partitional clustering method. The k-means algorithm requires many hours to get k clusters, because of large amounts of data. In this paper we propose a new method of k-means clustering using the grid-based sample. It reduce running time by using grid-based sample and keeps accuracy by using a center of gravity.


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