Klasterizacija metodom K-srednjih vrednosti (Serbian Wikipedia)

Dasgupta, S. & Freund, Y. (2009). „Random Projection Trees for Vector Quantization”. Information Theory, IEEE Transactions on. 55: 3229—3242. arXiv:0805.1390 . doi:10.1109/TIT.2009.2021326.

brinkster.com

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„Архивирана копија”. Архивирано из оригинала 23. 10. 2007. г. Приступљено 23. 10. 2007.

cam.ac.uk

inference.phy.cam.ac.uk

MacKay, David (2003). „Chapter 20. An Example Inference Task: Clustering” (PDF). Information Theory, Inference and Learning Algorithms. Cambridge University Press. str. 284—292. ISBN 978-0-521-64298-9. MR 2012999.

cmu.edu

cs.cmu.edu

Csurka, Gabriella; Dance, Christopher C.; Fan, Lixin; Willamowski, Jutta; Bray, Cédric (2004). Visual categorization with bags of keypoints (PDF). ECCV Workshop on Statistical Learning in Computer Vision.

code.google.com

http://code.google.com/p/figue/ FIGUE

codehaus.org

dist.codehaus.org

„Архивирана копија”. Архивирано из оригинала 09. 07. 2012. г. Приступљено 09. 07. 2012.

codingplayground.blogspot.com

Antonio Gulli's coding playground: K-means in C

doi.org

Lloyd, S. P. (1957). „Least square quantization in PCM”. Bell Telephone Laboratories Paper. Published in journal much later: Lloyd., S. P. (1982). „Least squares quantization in PCM” (PDF). IEEE Transactions on Information Theory. 28 (2): 129—137. doi:10.1109/TIT.1982.1056489. Pristupljeno 15. 4. 2009.
Vattani., A. (2011). „k-means requires exponentially many iterations even in the plane” (PDF). Discrete and Computational Geometry. 45 (4): 596—616. doi:10.1007/s00454-011-9340-1.
Aloise, D.; Deshpande, A.; Hansen, P.; Popat, P. (2009). „NP-hardness of Euclidean sum-of-squares clustering”. Machine Learning. 75: 245—249. doi:10.1007/s10994-009-5103-0.
Dasgupta, S. & Freund, Y. (2009). „Random Projection Trees for Vector Quantization”. Information Theory, IEEE Transactions on. 55: 3229—3242. arXiv:0805.1390 . doi:10.1109/TIT.2009.2021326.
Mahajan, M.; Nimbhorkar, P.; Varadarajan, K. (2009). „The Planar k-Means Problem is NP-Hard”. Lecture Notes in Computer Science. 5431: 274—285. doi:10.1007/978-3-642-00202-1_24.
Inaba, M.; Katoh, N.; Imai, H. (1994). Applications of weighted Voronoi diagrams and randomization to variance-based k-clustering. Proceedings of 10th ACM Symposium on Computational Geometry. str. 332—339. doi:10.1145/177424.178042.
Kanungo, T.; et al. (2002). „An efficient k-means clustering algorithm: Analysis and implementation” (PDF). IEEE Trans. Pattern Analysis and Machine Intelligence. 24: 881—892. doi:10.1109/TPAMI.2002.1017616. Pristupljeno 24. 4. 2009.
Amorim, R. C.; Mirkin, B (2012). „Minkowski metric, feature weighting and anomalous cluster initializing in K-Means clustering”. Pattern Recognition. 45 (3): 1061—1075. doi:10.1016/j.patcog.2011.08.012.
Honarkhah, Mehrdad; Caers, Jef (2010). „Stochastic Simulation of Patterns Using Distance-Based Pattern Modeling”. Mathematical Geosciences. 42 (5): 487—517. Bibcode:2010MaGeo..42..487H. S2CID 73657847. doi:10.1007/s11004-010-9276-7.

frahling.de

Frahling, G.; Sohler, C. (2006). „A fast k-means implementation using coresets” (PDF). Proceedings of the twenty-second annual symposium on Computational geometry (SoCG). Arhivirano iz originala (PDF) 5. 7. 2010. g.

gatech.edu

cc.gatech.edu

Drineas, P.; A. Frieze; et al. (2004). „Clustering large graphs via the singular value decomposition” (PDF). Machine learning. 56: 9—33. Pristupljeno 2. 8. 2012.

github.com

„reddavis/K-Means · GitHub[[Категорија:Ботовски наслови]]”. GitHub. Архивирано из оригинала 08. 07. 2012. г. Приступљено 08. 07. 2012. Сукоб URL—викивеза (помоћ)

harvard.edu

adsabs.harvard.edu

Honarkhah, Mehrdad; Caers, Jef (2010). „Stochastic Simulation of Patterns Using Distance-Based Pattern Modeling”. Mathematical Geosciences. 42 (5): 487—517. Bibcode:2010MaGeo..42..487H. S2CID 73657847. doi:10.1007/s11004-010-9276-7.

informationandvisualization.de

k-Means and Voronoi Tesselation: Built with Processing | Information & Visualization

javaworld.com

[„Hyper-threaded Java - JavaWorld[[Категорија:Ботовски наслови]]”. Архивирано из оригинала 02. 06. 2013. г. Приступљено 01. 06. 2013. Сукоб URL—викивеза (помоћ) Hyper-threaded Java - JavaWorld]

jstor.org

Hartigan, J. A.; Wong, M. A. (1979). „Algorithm AS 136: A K-Means Clustering Algorithm”. Journal of the Royal Statistical Society, Series C. 28 (1): 100—108. JSTOR 2346830.

le.ac.uk

math.le.ac.uk

E.M. Mirkes, K-means and K-medoids applet Архивирано на сајту Wayback Machine (29. мај 2013). University of Leicester, 2011.

leet.it

Color clustering

lwebzem.com

„Perl script for Kmeans clustering[[Категорија:Ботовски наслови]]”. Архивирано из оригинала 18. 06. 2012. г. Приступљено 01. 06. 2013. Сукоб URL—викивеза (помоћ)

maxlittle.net

Little, M.A.; Jones, N.S. (2011). „Generalized Methods and Solvers for Piecewise Constant Signals: Part I” (PDF). Proc. Roy. Soc. A.

mq.edu.au

web.science.mq.edu.au

„Interactive Demo of figue[[Категорија:Ботовски наслови]]”. Архивирано из оригинала 06. 07. 2011. г. Приступљено 06. 07. 2011. Сукоб URL—викивеза (помоћ)

nrbook.com

apps.nrbook.com

Press, WH; Teukolsky, SA; Vetterling, WT; Flannery, BP (2007). „Section 16.1. Gaussian Mixture Models and k-Means Clustering”. Numerical Recipes: The Art of Scientific Computing (3rd izd.). New York: Cambridge University Press. ISBN 978-0-521-88068-8.

polimi.it

home.dei.polimi.it

Clustering - K-means demo

projecteuclid.org

MacQueen, J. B. (1967). Some Methods for classification and Analysis of Multivariate Observations. Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability. 1. University of California Press. str. 281—297. MR 0214227. Zbl 0214.46201. Pristupljeno 7. 4. 2009.

psu.edu

citeseerx.ist.psu.edu

Schwenker, Friedhelm; Kestler, Hans A.; Palm, Günther (2001). „Three learning phases for radial-basis-function networks”. Neural Networks. 14: 439—458.

r-statistics.com

Clustergram: visualization and diagnostics for cluster analysis (R code) | R-statistics blog

revoledu.com

people.revoledu.com

scipy.org

docs.scipy.org

K-means clustering and vector quantization (scipy.cluster.vq) — SciPy v0.11 Reference Guide (DRAFT)

semanticscholar.org

api.semanticscholar.org

Honarkhah, Mehrdad; Caers, Jef (2010). „Stochastic Simulation of Patterns Using Distance-Based Pattern Modeling”. Mathematical Geosciences. 42 (5): 487—517. Bibcode:2010MaGeo..42..487H. S2CID 73657847. doi:10.1007/s11004-010-9276-7.

siebn.de

siebn.de - YAK-Means

stanford.edu

Coates, Adam; Ng, Andrew Y. (2012). „Learning feature representations with k-means” (PDF). Ур.: G. Montavon, G. B.; et al. Neural Networks: Tricks of the Trade. Springer. Архивирано из оригинала (PDF) 6. 6. 2013. г.

toronto.edu

cs.toronto.edu

Lloyd, S. P. (1957). „Least square quantization in PCM”. Bell Telephone Laboratories Paper. Published in journal much later: Lloyd., S. P. (1982). „Least squares quantization in PCM” (PDF). IEEE Transactions on Information Theory. 28 (2): 129—137. doi:10.1109/TIT.1982.1056489. Pristupljeno 15. 4. 2009.

ucsd.edu

charlotte.ucsd.edu

Hamerly, G. & Elkan, C. (2002). „Alternatives to the k-means algorithm that find better clusterings” (PDF). Proceedings of the eleventh international conference on Information and knowledge management (CIKM). Arhivirano iz originala (PDF) 7. 11. 2006. g.

cseweb.ucsd.edu

Vattani., A. (2011). „k-means requires exponentially many iterations even in the plane” (PDF). Discrete and Computational Geometry. 45 (4): 596—616. doi:10.1007/s00454-011-9340-1.

www-cse.ucsd.edu

Elkan, C. (2003). „Using the triangle inequality to accelerate k-means” (PDF). Proceedings of the Twentieth International Conference on Machine Learning (ICML).

umd.edu

cs.umd.edu

Kanungo, T.; et al. (2002). „An efficient k-means clustering algorithm: Analysis and implementation” (PDF). IEEE Trans. Pattern Analysis and Machine Intelligence. 24: 881—892. doi:10.1109/TPAMI.2002.1017616. Pristupljeno 24. 4. 2009.

uta.edu

ranger.uta.edu

H. Zha; et al. (2001). „Spectral Relaxation for K-means Clustering” (PDF). Neural Information Processing Systems vol.14 (NIPS 2001). Vancouver, Canada: 1057—1064.
Ding, Chris; Xiaofeng He (2004). „K-means Clustering via Principal Component Analysis” (PDF). Proc. of Int'l Conf. Machine Learning (ICML 2004): 225—232.

web.archive.org

Hamerly, G. & Elkan, C. (2002). „Alternatives to the k-means algorithm that find better clusterings” (PDF). Proceedings of the eleventh international conference on Information and knowledge management (CIKM). Arhivirano iz originala (PDF) 7. 11. 2006. g.
Frahling, G.; Sohler, C. (2006). „A fast k-means implementation using coresets” (PDF). Proceedings of the twenty-second annual symposium on Computational geometry (SoCG). Arhivirano iz originala (PDF) 5. 7. 2010. g.
E.M. Mirkes, K-means and K-medoids applet Архивирано на сајту Wayback Machine (29. мај 2013). University of Leicester, 2011.
Coates, Adam; Ng, Andrew Y. (2012). „Learning feature representations with k-means” (PDF). Ур.: G. Montavon, G. B.; et al. Neural Networks: Tricks of the Trade. Springer. Архивирано из оригинала (PDF) 6. 6. 2013. г.
„Архивирана копија”. Архивирано из оригинала 23. 10. 2007. г. Приступљено 23. 10. 2007.
„Perl script for Kmeans clustering[[Категорија:Ботовски наслови]]”. Архивирано из оригинала 18. 06. 2012. г. Приступљено 01. 06. 2013. Сукоб URL—викивеза (помоћ)
https://web.archive.org/web/20110607074701/http://www.cs.princeton.edu/~wdong/kmeans/
[„Hyper-threaded Java - JavaWorld[[Категорија:Ботовски наслови]]”. Архивирано из оригинала 02. 06. 2013. г. Приступљено 01. 06. 2013. Сукоб URL—викивеза (помоћ) Hyper-threaded Java - JavaWorld]

wikipedia.org

en.wikipedia.org

MacQueen, J. B. (1967). Some Methods for classification and Analysis of Multivariate Observations. Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability. 1. University of California Press. str. 281—297. MR 0214227. Zbl 0214.46201. Pristupljeno 7. 4. 2009.
Steinhaus, H. (1957). „Sur la division des corps matériels en parties”. Bull. Acad. Polon. Sci. 4 (12): 801—804. MR 0090073. Zbl 0079.16403.
MacKay, David (2003). „Chapter 20. An Example Inference Task: Clustering” (PDF). Information Theory, Inference and Learning Algorithms. Cambridge University Press. str. 284—292. ISBN 978-0-521-64298-9. MR 2012999.

zbmath.org

MacQueen, J. B. (1967). Some Methods for classification and Analysis of Multivariate Observations. Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability. 1. University of California Press. str. 281—297. MR 0214227. Zbl 0214.46201. Pristupljeno 7. 4. 2009.
Steinhaus, H. (1957). „Sur la division des corps matériels en parties”. Bull. Acad. Polon. Sci. 4 (12): 801—804. MR 0090073. Zbl 0079.16403.