Automatic Determination of Clustering Centers for “Clustering by Fast Search and Find of Density Peaks”
نویسندگان
چکیده
منابع مشابه
An Adaptive Method for Clustering by Fast Search-and-Find of Density Peaks: Adaptive-DP
Clustering by fast search and find of density peaks (DP) is a method in which density peaks are used to select the number of cluster centers. The DP has two input parameters: 1) the cutoff distance and 2) cluster centers. Also in DP, different methods are used to measure the density of underlying datasets. To overcome the limitations of DP, an Adaptive-DP method is proposed. In Adaptive-DP meth...
متن کاملComment on "Clustering by fast search and find of density peaks"
Shuliang Wang, Dakui Wang, Caoyuan Li, Yan Li School of software, Beijing Institute of Technology, Beijing, China International School of Software, Wuhan University, Wuhan, China Email: [email protected] Abstract. In [1], a clustering algorithm was given to find the centers of clusters quickly. However, the accuracy of this algorithm heavily depend on the threshold value of dc . Furthermore...
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CFSFDP (clustering by fast search and find of density peaks) is recently developed density-based clustering algorithm. Compared to DBSCAN, it needs less parameters and is computationally cheap for its noniteration. Alex. at al have demonstrated its power by many applications. However, CFSFDP performs not well when there are more than one density peak for one cluster, what we name as "no density...
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ژورنال
عنوان ژورنال: Mathematical Problems in Engineering
سال: 2020
ISSN: 1024-123X,1563-5147
DOI: 10.1155/2020/4724150