Multi-feature weighting neighborhood density clustering

Author:

Xu Shuliang,Feng LinORCID,Liu Shenglan,Zhou Jian,Qiao Hong

Funder

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Reference52 articles.

1. An S, Hu Q, Yu D (2015) Robust rough set and applications. Tsinghua University Press, Beijing

2. Arthur D, Vassilvitskii S (2007) k-means++: the advantages of careful seeding. In: Proceedings of the eighteenth annual ACM-SIAM symposium on discrete algorithms. Society for Industrial and Applied Mathematics, pp 1027–1035

3. Bai L, Liang J, Dang C, Cao F (2013) The impact of cluster representatives on the convergence of the k-modes type clustering. IEEE Trans Pattern Anal Mach Intell 35(6):1509–1522

4. Belkin M, Niyogi P (2002) Laplacian eigenmaps and spectral techniques for embedding and clustering. Advances in neural information processing systems. MIT Press, Cambridge, pp 585–591

5. Berkhin P (2006) A survey of clustering data mining techniques. In: Kogan J, Nicholas C, Teboulle M (eds) Grouping multidimensional data. Springer, Berlin, pp 25–71

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