On Knowledge Granulation and Applications to Classifier Induction in the Framework of Rough Mereology

Knowledge granulation as proposed by Zadeh consists in making objects under discussion into classes called granules; objects within a granule are similar one to another to a satisfactory degree relative to a chosen similarity measure. Rough mereology as developed by Polkowski in a series of works is...

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Bibliographic Details
Published in:	International Journal of Computational Intelligence Systems
Main Authors:	Lech Polkowski, Piotr Artiemjew
Format:	Article
Language:	English
Published:	Springer 2009-12-01
Subjects:	rough sets knowledge granulation rough mereology rough inclusions classification of data into categories granular data sets and classifiers
Online Access:	https://www.atlantis-press.com/article/1890.pdf

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