pyclustering
0.10.1
pyclustring is a Python, C++ data mining library.
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Johannes Agrawal, Rakeshand Gehrke, Dimitrios Gunopulos, and Prabhakar Raghavan. Automatic subspace clustering of high dimensional data. Data Mining and Knowledge Discovery, 11(1):5–33, Jul 2005.
Mihael Ankerst, Markus M. Breunig, Hans-Peter Kriegel, and Jorg Sander. Optics: Ordering points to identify the clustering structure. SIGMOD Rec., 28(2):49–60, June 1999.
Alex Arenas, Albert Diaz-Guilera, Jurgen Kurths, Yamir Moreno, and Changsong Zhou. Synchronization in complex networks. Physics Reports, 469(3):93–153, 12 2008.
David Arthur and Sergei Vassilvitskii. K-means++: the advantages of careful seeding. In In Proceedings of the 18th Annual ACM-SIAM Symposium on Discrete Algorithms, 2007.
Elena N. Benderskaya and Sofya V. Zhukova. Clustering by chaotic neural networks with mean field calculated via delaunay triangulation. In Emilio Corchado, Ajith Abraham, and Witold Pedrycz, editors, Hybrid Artificial Intelligence Systems, pages 408–416, Berlin, Heidelberg, 2008. Springer Berlin Heidelberg.
E. N. Benderskaya and S. V. Zhukova. Large-dimension image clustering by means of fragmentary synchronization in chaotic systems. Pattern Recognition and Image Analysis, 19(2):306–314, Jun 2009.
James C. Bezdek. Pattern Recognition with Fuzzy Objective Function Algorithms. Kluwer Academic Publishers, Norwell, MA, USA, 1981.
Daniel Brelaz. New methods to color the vertices of a graph. Commun. ACM, 22(4):251–256, April 1979.
David Chik, Roman Borisyuk, and Yakov Kazanovich. Selective attention model with spiking elements. Neural Networks, 22(7):890 – 900, 2009.
M.C. Cowgill, R.J. Harvey, and L.T. Watson. A genetic algorithm approach to cluster analysis. Computers & Mathematics with Applications, 37(7):99 – 108, 1999.
Martin Ester, Hans-Peter Kriegel, Jorg Sander, and Xiaowei Xu. A density-based algorithm for discovering clusters a density-based algorithm for discovering clusters in large spatial databases with noise. In Proceedings of the Second International Conference on Knowledge Discovery and Data Mining, KDD'96, pages 226–231. AAAI Press, 1996.
R. Follmann, E. E. N. Macau, E. Rosa, and J. R. C. Piqueira. Phase oscillatory network and visual pattern recognition. IEEE Transactions on Neural Networks and Learning Systems, 26(7):1539–1544, July 2015.
J. C. Gower. A general coefficient of similarity and some of its properties. Biometrics, 27(4):857–871, December 1971.
Sudipto Guha, Rajeev Rastogi, and Kyuseok Shim. Cure: An efficient clustering algorithm for large databases. SIGMOD Rec., 27(2):73–84, June 1998.
S. Guha, R. Rastogi, and K. Shim. Rock: A robust clustering algorithm for categorical attributes. In Proceedings of the 15th International Conference on Data Engineering, ICDE '99, pages 512–, Washington, DC, USA, 1999. IEEE Computer Society.
Maya R. Gupta and Yihua Chen. Theory and use of the em algorithm. Found. Trends Signal Process., 4(3):223–296, March 2011.
Greg Hamerly and Charles Elkan. Learning the k in k-means. In Proceedings of the 16th International Conference on Neural Information Processing Systems, NIPS'03, pages 281–288, Cambridge, MA, USA, 2003. MIT Press.
Anil K. Jain and Richard C. Dubes. Algorithms for Clustering Data. Prentice-Hall, Inc., Upper Saddle River, NJ, USA, 1988.
Kenya Jinnno. Dynamical hysteresis neural networks for graph coloring problem. 2009:331–340, 02 2009.
Kenya Jin'no. Dynamical hysteresis neural networks for graph coloring problem. pages 331–340, 2009.
T. Kohonen, E. Oja, O. Simula, A. Visa, and J. Kangas. Engineering applications of the self-organizing map. Proceedings of the IEEE, 84(10):1358–1384, Oct 1996.
T. Kohonen. The self-organizing map. volume 78, pages 1464–1480, Sep 1990.
Yoshiki Kuramoto. Chemical oscillations, waves, and turbulence. Chemistry Series. Dover Publications, 2003. originally published: Springer Berlin, New York, Heidelberg, 1984.
Thomas Lindblad and Jason M. Kinser. Image Processing using Pulse-Coupled Neural Networks. Springer-Verlag, Berlin, Heidelberg, 3rd edition, 2013.
X. B. Lu and B. Z. Qin. Adaptive cluster synchronization in coupled phase oscillators. In 2009 International Conference on Information Engineering and Computer Science, pages 1–4, Dec 2009.
J. Macqueen. Some methods for classification and analysis of multivariate observations. In In 5-th Berkeley Symposium on Mathematical Statistics and Probability, pages 281–297, 1967.
Ujjwal Maulik and Sanghamitra Bandyopadhyay. Genetic algorithm-based clustering technique. Pattern Recognition, 33(9):1455 – 1465, 2000.
Raymond T. Ng and Jiawei Han. Clarans: A method for clustering objects for spatial data mining. IEEE Transactions on Knowledge and Data Engineering, 14(5):1003–1016, 2002.
A. V. Novikov and E. N. Benderskaya. Oscillatory neural networks based on the kuramoto model for cluster analysis. Pattern Recognit. Image Anal., 24(3):365–371, September 2014.
A. V. Novikov and E. N. Benderskaya. Sync-som double-layer oscillatory network for cluster analysis. In Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods, ICPRAM 2014, pages 305–309, Portugal, 2014. SCITEPRESS - Science and Technology Publications, Lda.
Andrei Novikov and Elena Benderskaya. Oscillatory network based on kuramoto model for image segmentation. In Proceedings of the 13th International Conference on Parallel Computing Technologies - Volume 9251, pages 210–221, New York, NY, USA, 2015. Springer-Verlag New York, Inc.
Dan Pelleg and Andrew W. Moore. X-means: Extending k-means with efficient estimation of the number of clusters. In Proceedings of the Seventeenth International Conference on Machine Learning, ICML '00, pages 727–734, San Francisco, CA, USA, 2000. Morgan Kaufmann Publishers Inc.
Peter Rousseeuw. Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. J. Comput. Appl. Math., 20(1):53–65, November 1987.
Hanan Samet. The Design and Analysis of Spatial Data Structures. Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA, 1990.
Erich Schikuta and Martin Erhart. Bang-clustering: A novel grid-clustering algorithm for huge data sets. In Adnan Amin, Dov Dori, Pavel Pudil, and Herbert Freeman, editors, Advances in Pattern Recognition, pages 867–874, Berlin, Heidelberg, 1998. Springer Berlin Heidelberg.
Erich Schubert and Peter J. Rousseeuw. Faster k-medoids clustering: Improving the pam, clara, and clarans algorithms. In Similarity Search and Applications, pages 171–187, Cham, 2019. Springer International Publishing.
M. Shahbaba and S. Beheshti. Improving x-means clustering with mndl. In 2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA), pages 1298–1302, 2012.
J. Shao, X. He, C. Böhm, Q. Yang, and C. Plant. Synchronization-inspired partitioning and hierarchical clustering. IEEE Transactions on Knowledge and Data Engineering, 25(4):893–905, April 2013.
Sergios Theodoridis and Konstantinos Koutroumbas. Pattern Recognition, fourth edition. Elsevier, 2009.
Robert L. Thorndike. Who belongs in the family?. Psychometrika, 18(4):267–276, Dec 1953.
Jeffrey S. Vitter. Random sampling with a reservoir. ACM Trans. Math. Softw., 11(1):37–57, March 1985.
DeLiang Wang and D. Terman. Locally excitatory globally inhibitory oscillator networks. IEEE Transactions on Neural Networks, 6(1):283–286, Jan 1995.
DeLiang Wang and David Terman. Image segmentation based on oscillatory correlation. Neural Comput., 9(4):805–836, May 1997.
Jianshe Wu, Licheng Jiao, Rui Li, and Weisheng Chen. Clustering dynamics of nonlinear oscillator network: Application to graph coloring problem. Physica D: Nonlinear Phenomena, 240(24):1972 – 1978, 2011.
Tian Zhang, Raghu Ramakrishnan, and Miron Livny. Birch: An efficient data clustering method for very large databases. SIGMOD Rec., 25(2):103–114, June 1996.