Abstract
Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense or another) to each other than to those in other groups (clusters). It is a main task of exploratory data mining, and a common technique for statistical data analysis, used in many fields, including machine learning, pattern recognition, image analysis, information retrieval, bioinformatics, data compression, and computer graphics.
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References
Manly, B.F.J.: Multivariate Statistical Methods: A Primer, 3rd edn. Chapman and Hall, London (2005)
Everitt, B.S., Landau, S., Leese, M.: Cluster Analysis, 4th edn. Arnold, London (2001)
Rencher, A.C.: Methods of Multivariate Analysis, 2nd edn. Wiley, Hoboken (2002)
Chavent, M.: An hausdorff distance between hyper-rectangles for clustering interval data. In: Banks, D., House, L., McMorris, F., Arabie, P., Gaul, W. (eds.) Classification, Clustering, and Data Mining Applications. Springer, Berlin (2004)
Veres, O., Shakhovska, N.: Elements of the formal model big date. In: Perspective Technologies and Methods in MEMS Design, MEMSTECH (2015)
De Souza, R.M.C.R., De Carvalho, F.A.T.: Clustering of interval data based on city-block distances. Pattern Recognit. Lett. 25(3), 353 (2004)
Gordon, A.D.: An iteractive relocation algorithm for classifying symbolic data. In: Gaul, W.E.A. (ed.) Data Analysis: Scientific Modeling and Practical Application. Springer, Berlin (2000)
Dokshitzer, Y.L., et al.: Better jet clustering algorithms. J. High Energy Phys. 1997, 1 (1997)
Cai, W., Chen, S., Zhang, D.: Fast and robust fuzzy c-means clustering algorithms incorporating local information for image segmentation. Pattern Recognit. 40(3), 825–838 (2007)
Da Jiao, Z.L.Z.W., Cheng, L.: Kernel clustering algorithm. Chin. J. Comput. 6, 004 (2002)
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Zheliznyak, I., Rybchak, Z., Zavuschak, I. (2017). Analysis of Clustering Algorithms. In: Shakhovska, N. (eds) Advances in Intelligent Systems and Computing. Advances in Intelligent Systems and Computing, vol 512. Springer, Cham. https://doi.org/10.1007/978-3-319-45991-2_21
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DOI: https://doi.org/10.1007/978-3-319-45991-2_21
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