计算机与现代化
計算機與現代化
계산궤여현대화
COMPUTER AND MODERNIZATION
2014年
11期
90-93,97
,共5页
网格聚类%增量聚类%多密度%单元%判别函数
網格聚類%增量聚類%多密度%單元%判彆函數
망격취류%증량취류%다밀도%단원%판별함수
grid clustering%incremental clustering%multi-density%cell%discriminant function
提出一种基于网格的多密度增量聚类算法MICG,定义含网格单元间的相对密度和重心距离的判别函数。当数据集的部分数据发生变动后,不需要对全部数据重新聚类,只需分析有数据变更的单元与邻居单元的关系,结合原有的聚类结果形成新的聚类,有效地提高了聚类分析的效率。时间复杂度与空间复杂度同数据集大小、属性个数成线性关系。实验结果表明,MICG算法能够处理任意形状和不同密度的类,有效地解决数据更新时的增量聚类问题。
提齣一種基于網格的多密度增量聚類算法MICG,定義含網格單元間的相對密度和重心距離的判彆函數。噹數據集的部分數據髮生變動後,不需要對全部數據重新聚類,隻需分析有數據變更的單元與鄰居單元的關繫,結閤原有的聚類結果形成新的聚類,有效地提高瞭聚類分析的效率。時間複雜度與空間複雜度同數據集大小、屬性箇數成線性關繫。實驗結果錶明,MICG算法能夠處理任意形狀和不同密度的類,有效地解決數據更新時的增量聚類問題。
제출일충기우망격적다밀도증량취류산법MICG,정의함망격단원간적상대밀도화중심거리적판별함수。당수거집적부분수거발생변동후,불수요대전부수거중신취류,지수분석유수거변경적단원여린거단원적관계,결합원유적취류결과형성신적취류,유효지제고료취류분석적효솔。시간복잡도여공간복잡도동수거집대소、속성개수성선성관계。실험결과표명,MICG산법능구처리임의형상화불동밀도적류,유효지해결수거경신시적증량취류문제。
This paper presents a multi-density incremental clustering algorithm based on grid ( MICG) , the discriminant function taking into account relative density and gravity distance between grid cells is introduced. When a portion of the data sets changed, without re-clustering all the data, this algorithm could formulate a new cluster according to original clustering result merely based on the relationship between the unit with changed data set and neighbored unit. This approach effectively improved efficiency of cluster analysis. The time complexity and space complexity are linear with the size of dataset and the number of attributes. The experimental results show that MICG algorithm can process cluster with any shape or different densities, and can solve the incre-ment clustering problem effectively when the data is updated.
