Abstract
In the paper, in the Rough Extended Framework, a new generalization of the concept of the rough transformation has been presented. The introduced solution seems to present promising area of data analysis, particulary suited in the area of image properties analysis. The uniform RECA transformation as a generalization of clustering approaches contains three standard rough transformations - standard k-means transformation, fuzzy k-means transformation and EM k-means transformation. The concept of the RECA transformations has been illustrated with its application in the procedure of calculation of the entropy of the RECA transformation paths. In this way, uniform RECA transformations give both the theoretical ground for three most prominent data clustering schemes and at the same time present starting point in the new data analysis methodology based upon the new introduced concept of RECA paths.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Malyszko, D., Stepaniuk, J.: Granular Multilevel Rough Entropy Thresholding in 2D Domain. In: 16th International Conference Intelligent Information Systems, IIS 2008, Zakopane, Poland, June 16-18, pp. 151–160 (2008)
Małyszko, D., Stepaniuk, J.: Standard and Fuzzy Rough Entropy Clustering Algorithms in Image Segmentation. In: Chan, C.-C., Grzymala-Busse, J.W., Ziarko, W.P. (eds.) RSCTC 2008. LNCS (LNAI), vol. 5306, pp. 409–418. Springer, Heidelberg (2008)
Malyszko, D., Stepaniuk, J.: Adaptive multilevel rough entropy evolutionary thresholding. Information Sciences 180(7), 1138–1158 (2010)
Malyszko, D., Stepaniuk, J.: Adaptive Rough Entropy Clustering Algorithms in Image Segmentation. Fundamenta Informaticae 98(2-3), 199–231 (2010)
Pal, S.K., Shankar, B.U., Mitra, P.: Granular computing, rough entropy and object extraction. Pattern Recognition Letters 26(16), 2509–2517 (2005)
Pawlak, Z., Skowron, A.: Rudiments of rough sets. Information Sciences 177(1), 3–27 (2007)
Pedrycz, W., Skowron, A., Kreinovich, V. (eds.): Handbook of Granular Computing. John Wiley & Sons, New York (2008)
Skowron, A., Stepaniuk, J.: Tolerance Approximation Spaces. Fundamenta Informaticae 27(2-3), 245–253 (1996)
Stepaniuk, J.: Rough–Granular Computing in Knowledge Discovery and Data Mining. Springer, Heidelberg (2008)
Slezak, D., Ziarko, W.: The investigation of the Bayesian rough set model. International Journal of Approximate Reasoning 40, 81–91 (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Małyszko, D., Stepaniuk, J. (2011). Uniform RECA Transformations in Rough Extended Clustering Framework. In: Nguyen, N.T., Kim, CG., Janiak, A. (eds) Intelligent Information and Database Systems. ACIIDS 2011. Lecture Notes in Computer Science(), vol 6592. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20042-7_12
Download citation
DOI: https://doi.org/10.1007/978-3-642-20042-7_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-20041-0
Online ISBN: 978-3-642-20042-7
eBook Packages: Computer ScienceComputer Science (R0)