assigned to any well defined particle class for this sample. However, it must be noted that thehierarchical method is simple in terms of computational scheme, and is flexible in terms of decision on the assignment to significant clusters by simply shifting the clustering level in the same ...
The source clustering is achieved by incorporation of supersaturated vapor of cluster material in a flow ofinert gasat low temperature andhigh pressurein this method. The vaporization may be carried out by magnetic sputtering. At low temperatures, the cluster is generated by the successive addition ...
DPCG: an efficient density peaks clustering algorithm based on grid. Xu X,Ding S,Du M, et al. International Journal of Machine Learning .&.Cybernetics . 2016X. Xu, S. Ding, M. Du, Y. Xue, DPCG: an efficient density peaks clustering algorithm based on grid, Int. J. Mach. Learn....
But unfortunately, we need to calculate the distance between all data points in the first process, which limits the running speed of DPC algorithm on large datasets. To address this issue, this paper introduces a novel approach based on grid, called density peaks clustering algorithm based on ...
This model can effectively handle network anomaly detection based on massive network traffic data. 2. We propose an improved density peaks clustering (DPC) algorithm called DPC-GS-MND, which combines the DPC algorithm with grid screening and mutual neighborhood degree to improve the accuracy and ...
Moreover, a new non-center point's allocation strategy and the cluster merging and splitting processes are developed to adapt to the density peaks and adjust the clusters dynamically, which can improve the clustering accuracy and scalability. The ICFS method is evaluated on several datasets by ...
Clustering by fast search and find of density peaks (shorted as DPC) is a powerful clustering algorithm. However it has a fatal problem that once a point is assigned erroneously, then there may be...doi:10.1007/978-3-319-97310-4_36Juanying Xie...
Unsupervised clustering algorithm is successfully applied in many fields. While the method of fast search and find of density peaks can efficiently discover the centers of clusters by finding the high-density peaks, it suffers from selecting the cluster center manually which depends legitimately on sub...
Section “Approach overview” provides a brief introduction to the proposed policy evaluation engine, named DPEngine. In section “An effective policy evaluation engine”, we discuss an improved clustering algorithm and the details of the DPEngine. Section “Experimental results and analyses” shows ...
Houlahan and Scalo (1992) introduced the hierarchical clustering method to the study of the internal structure of molecular clouds for the first time. The dendrogram based on the molecular cloud column density and applied to the Taurus complex reveals a hierarchical structure in the star-forming mol...