Boundary Points Detecting Algorithm for Clusters in Noisy Dataset
Yue Jiang Feng, Baozhi Qiu · Jisuanji gongcheng · 2007
In order to detect boundary points of clusters effectively,a technique making use of objects’ density and distribution feature in its Eps-neighborhood to detect boundary points,and a boundary points detecting algorithm named BOUND(detecting boundary points of clusters in noisy dataset) is developed.Experimental results show that BOUND can detect boundary points in noisy dataset containing different shapes and sizes clusters effectively and efficiently.