24. 参考 [3/6]
Lloyd
◦ Lloyd, S. Least squares quantization in PCM. IEEE Transactions on Information Theory 28(2), 129–137, Mar
1982.
[https://dx.doi.org/10.1109/TIT.1982.1056489] (有料)
Forgy
◦ E.W. Forgy. Cluster analysis of multivariate data: efficiency versus interpretability of classifications.
Biometrics 21: 768–769. 1965. (URL 不明)
MacQueen
◦ MacQueen, J. Some methods for classification and analysis of multivariate observations. Proceedings of
the Fifth Berkeley Symposium on Mathematical Statistics and Probability, Volume 1: Statistics, 281–297,
University of California Press, Berkeley, Calif., 1967.
[http://projecteuclid.org/download/pdf_1/euclid.bsmsp/1200512992]
Hartigan-Wong
◦ J. A. Hartigan and M. A. Wong. Algorithm AS 136: A K-Means Clustering Algorithm. Journal of the Royal
Statistical Society. Series C (Applied Statistics), Vol. 28, No. 1 (1979), pp. 100-108.
[http://www.jstor.org/stable/2346830] (有料)
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25. 参考 [4/6]
Hartigan-Wong の方法を説明している論文
◦ Noam Slonim, Ehud Aharoni, Koby Crammer. Hartigan’s K-Means Versus Lloyd’s K-Means - Is It Time for a
Change? IJCAI 2013.
[http://ijcai.org/papers13/Papers/IJCAI13-249.pdf]
◦ Matus Telgarsky, Andrea Vattani. Hartigan’s Method: k-means Clustering without Voronoi. AISTATS 2010.
[http://jmlr.csail.mit.edu/proceedings/papers/v9/telgarsky10a/telgarsky10a.pdf]
k-means++
◦ David Arthur and Sergei Vassilvitskii. 2007. k-means++: the advantages of careful seeding. In Proceedings
of the eighteenth annual ACM-SIAM symposium on Discrete algorithms (SODA ‘07). Society for Industrial
and Applied Mathematics, Philadelphia, PA, USA, 1027-1035.
[http://dl.acm.org/citation.cfm?id=1283494] (有料)
[http://ilpubs.stanford.edu:8090/778/] (同じタイトルのテクニカルレポート)
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26. 参考 [5/6]
特に参考になったウェブ上の情報
◦ k-means return value in R
◦ http://stackoverflow.com/questions/8637460/k-means-return-value-in-r
◦ kmeans 関数の 'singleton' オプション
◦ http://d.hatena.ne.jp/nthrn/20081025/1224901102
◦ what’s the implementation of SciKit-Learn K-Means for empty clusters?
◦ http://stats.stackexchange.com/questions/152333/whats-the-implementation-of-scikit-
learn-k-means-for-empty-clusters
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