Description: Spectral clustering hasbeenusedto identify clustersthat arenonlinearly separableininput space, andusuallyoutper
formstraditional clustering algorithms. However, the performances of spectral clustering are severely dependent onvaluesof the
scaling parameter. Inthispaper, anadaptive spectral clustering(ASC) algorithmwasproposedbasedontraditional spectral clus
tering, whichcanchoose the scaling parameter automatically by using techniques similar to kernel selection. The newalgorithm
was comparedto existingparameter selectionbasedspectral clustering algorithmsonbothsyntheticandUCI datasets, andthe ex
perimental results validatethe effectivenessof theproposedalgorithm
To Search:
File list (Check if you may need any files):
自适应谱聚类算法研究.pdf
Download