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Alternative TitleClustering by fast search and find of density peaks based on spectrum analysis
韩忠华1,2; 毕开元1; 司雯1; 吕哲1
Source Publication计算机应用
Indexed ByCSCD
Contribution Rank1
Funding Organization国家自然科学基金资助项目( 61503259) ; 辽宁省科技厅面上项目( 201602608) ; 辽宁省高等学校基本科研项目( LJZ2017015) ; 辽宁省档案科技项目( L-2018-X-10)
Keyword数据聚类 适应性 降维 密度峰值快速聚类 谱分析
Other AbstractFor different clustering effects of Clustering by Fast Search and Find of Density Peaks ( CFSFDP) on different datasets,an improved CFSFDP algorithm based on spectral clustering was proposed,namely CFSFDP-SA ( CFSFDP based on Spectrum Analysis) . Firstly,a high-dimensional non-linear dataset was mapped into a low-dimensional subspace to realize dimension reduction,then the clustering problem was transformed into the optimal partitioning problem of the graph to enhance the algorithm adaptability to the global structure of the data. Secondly,the CFSFDP algorithm was used to cluster the processed dataset. Combining the advantages of these two clustering algorithms,the clustering performance was further improved. The clustering results of two artificial linear datasets,three artificial nonlinear datasets and four real datasets in UCI show that compared with CFSFDP,the CFSFDP-SA algorithm has higher clustering precision,achieving up to 14% improvement in accuracy for high-dimensional dataset,which means CFSFDP-SA is more adaptable to the original datasets.
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Document Type期刊论文
Corresponding Author毕开元
Recommended Citation
GB/T 7714
韩忠华,毕开元,司雯,等. 基于谱分析的密度峰值快速聚类算法[J]. 计算机应用,2019,39(2):409-413.
APA 韩忠华,毕开元,司雯,&吕哲.(2019).基于谱分析的密度峰值快速聚类算法.计算机应用,39(2),409-413.
MLA 韩忠华,et al."基于谱分析的密度峰值快速聚类算法".计算机应用 39.2(2019):409-413.
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