The running time of DFBC algorithm increases linearity with the increases of combinations. It’s actually a compromise of low-dimensional and high-dimensional clustering method on its idea.
该算法按照维组层次的增长,计算时间也是呈线性变化的,但是就算法的思想来说,它是低维聚类与高维聚类技术的一种折衷。
参考来源 - 高维数据聚类技术中的若干算法研究·2,447,543篇论文数据，部分数据来源于NoteExpress
To overcome the shortcomings of the GCOD, a high-dimensional clustering algorithm for data mining, the paper proposes an intersected grid clustering algorithm based on density estimation (IGCOD).
针对高维聚类算法——相交网格划分算法GCOD存在的缺陷，提出了基于密度度量的相交网格划分聚类算法IGCOD。
This paper introduces a newly generalized and dynamic structure for the similarity retrieval of high dimensional feature vectors called the recursive clustering index tree.
文章提出了一种新的适用于高维特征矢量相似检索动态聚类索引树结构。
It is hard to cluster high-dimensional data using traditional clustering algorithm because of the sparsity of data.
在高维空间中，由于数据的稀疏性，传统的聚类方法难以有效地聚类高维数据。
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