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- W4247465277 abstract "In the setting of pattern recognition, clustering is one of the dominant and well-delineated domains in this area having its own agenda and contributing results to the successive processing scheme, especially classifiers and predictors. This chapter focuses on a few representative examples present among numerous approaches being representative of objective function-based clustering and hierarchical clustering. The k-means clustering algorithm is one of the commonly considered clustering methods. In the sequel, the chapter identifies a role of information granules and underlines that clustering serves as a vehicle to construct granules. Furthermore it is shown that granular clustering concerns also ways of building clusters on a basis of data coming in the form of information granules. The chapter also demonstrates how the principle of justifiable information granularity contributes to the concise description of information granules built on a basis of results of clustering." @default.
- W4247465277 created "2022-05-12" @default.
- W4247465277 date "2018-02-09" @default.
- W4247465277 modified "2023-10-14" @default.
- W4247465277 title "CLUSTERING" @default.
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- W4247465277 doi "https://doi.org/10.1002/9781119302872.ch8" @default.
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