Abstract
Granular computing is a new paradigm in data mining. It mimics a procedure commonly used by humans. A data granule may be defined as a collection of related entities in sense of similarity, proximity, indiscernibility. Nowadays granular computing focuses on elaboration of granules from data. This step in granular computing is well researched. Our objective is the next step: we would like to focus on computing with granules. In the paper we propose a new clustering algorithm that works with granules instead of numbers. The algorithm takes a collection of granules as an input and clusters them into output granules.
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Acknowledgements
The research has been supported by the Rector’s Grant for Research and Development (Silesian University of Technology, grant number: 02/020/RGJ19/0165).
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Siminski, K. (2020). GrFCM – Granular Clustering of Granular Data. In: Gruca, A., Czachórski, T., Deorowicz, S., Harężlak, K., Piotrowska, A. (eds) Man-Machine Interactions 6. ICMMI 2019. Advances in Intelligent Systems and Computing, vol 1061 . Springer, Cham. https://doi.org/10.1007/978-3-030-31964-9_11
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DOI: https://doi.org/10.1007/978-3-030-31964-9_11
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