The global Minmax k-means algorithm
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Multidisciplinary
Link
http://link.springer.com/content/pdf/10.1186/s40064-016-3329-4.pdf
Reference22 articles.
1. Arthur D, Vassilvitskii S (2007) k-means++: the advantages of careful seeding. In: ACM-SIAM symposium on discrete algorithm (SODA), pp 1027–1035
2. Bagirov AM (2008) Modified global k-means algorithm for minimum sum-of-squares clustering problems. Pattern Recognit 41:3192–3199
3. Bagirov AM, Ugon J, Webb D (2011) Fast modified global k-means algorithm for incremental cluster construction. Pattern Recognit 44:866–876
4. Banerjee A, Ghosh J (2004) Frequency-sensitive competitive learning for scalable balanced clustering on high-dimensional hyperspheres. IEEE Trans Neural Netw 15(3):702–719
5. Berkhin P (2006) A survey of clustering data mIning techniques. In: Kogan J, Nicholas C, Teboulle M (eds) Grouping multidimensional data: recent advances in clustering. Springer, Berlin, pp 25–71
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