K-Means-Algorithmus (German Wikipedia)

Analysis of information sources in references of the Wikipedia article "K-Means-Algorithmus" in German language version.

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1projecteuclid.org

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1scikit-image.org

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dlib.net (Global: low place; German: low place)

dlib C++ Library - kkmeans_ex.cpp. Abgerufen am 8. Januar 2019.

doi.org (Global: 2^nd place; German: 3^rd place)

S. P. Lloyd: Least square quantization in PCM. In: Bell Telephone Laboratories Paper. 1957. , später erst in einer Zeitschrift:
S. P. Lloyd: Least squares quantization in PCM. In: IEEE Transactions on Information Theory. 2. Auflage. Band 28, 1982, S. 129–137, doi:10.1109/TIT.1982.1056489 (cs.toronto.edu [PDF; 1,3 MB; abgerufen am 15. April 2009]).
T. Kanungo, D. M. Mount, N. S. Netanyahu, C. D. Piatko, R. Silverman, A. Y. Wu: An efficient k-means clustering algorithm: Analysis and implementation. In: IEEE Trans. Pattern Analysis and Machine Intelligence. Vol. 24, 2002, S. 881–892, doi:10.1109/TPAMI.2002.1017616 (englisch, umd.edu [PDF; abgerufen am 24. April 2009]).

jstor.org (Global: 26^th place; German: 153^rd place)

J. A. Hartigan, M. A. Wong: Algorithm AS 136: A K-Means Clustering Algorithm. In: Journal of the Royal Statistical Society, Series C (Applied Statistics). 1. Auflage. Band 28, 1979, S. 100–108, JSTOR:2346830.

projecteuclid.org (Global: 3,707^th place; German: 5,342^nd place)

J. B. MacQueen: Some Methods for classification and Analysis of Multivariate Observations. In: Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability. Band 1. University of California Press, 1967, S. 281–297 (projecteuclid.org [abgerufen am 7. April 2009]).

scikit-image.org (Global: low place; German: low place)

Module: segmentation — skimage docs. Abgerufen am 8. September 2018 (englisch).

stanford.edu (Global: 179^th place; German: 460^th place)

theory.stanford.edu

David Arthur, Sergei Vassilvitskii: 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, Philadelphia, PA, USA 2007, ISBN 978-0-89871-624-5, S. 1027–1035 (stanford.edu [PDF; abgerufen am 27. März 2015]).

toronto.edu (Global: low place; German: 8,952^nd place)

cs.toronto.edu

S. P. Lloyd: Least square quantization in PCM. In: Bell Telephone Laboratories Paper. 1957. , später erst in einer Zeitschrift:
S. P. Lloyd: Least squares quantization in PCM. In: IEEE Transactions on Information Theory. 2. Auflage. Band 28, 1982, S. 129–137, doi:10.1109/TIT.1982.1056489 (cs.toronto.edu [PDF; 1,3 MB; abgerufen am 15. April 2009]).

ucsd.edu (Global: 1,933^rd place; German: 3,857^th place)

www-cse.ucsd.edu

C. Elkan: Using the triangle inequality to accelerate k-means. In: Proceedings of the Twentieth International Conference on Machine Learning (ICML). 2003 (ucsd.edu [PDF; 88 kB]).

umd.edu (Global: 1,747^th place; German: 1,498^th place)

cs.umd.edu

T. Kanungo, D. M. Mount, N. S. Netanyahu, C. D. Piatko, R. Silverman, A. Y. Wu: An efficient k-means clustering algorithm: Analysis and implementation. In: IEEE Trans. Pattern Analysis and Machine Intelligence. Vol. 24, 2002, S. 881–892, doi:10.1109/TPAMI.2002.1017616 (englisch, umd.edu [PDF; abgerufen am 24. April 2009]).
T. Kanungo, D. Mount, N. Netanyahux, C. Piatko, R. Silverman, A. Wu A Local Search Approximation Algorithm for k-Means Clustering. (PDF; 170 kB) In: Computational Geometry: Theory and Applications, 2004.