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Energy-Based Centroid Identification and Cluster Propagation with Noise Detection

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Computational Collective Intelligence (ICCCI 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11055))

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Abstract

Clustering algorithms are used to partition an existing set of objects into groups according to similarity of their attributes. Parametric algorithms for determining initial points (centroids) and subsequent cluster propagation are proposed. The principle of competitive growth of clusters due to the absorption of boundary (contiguous) objects is used. The object is absorbed by that cluster or transferred from an adjacent cluster if it maximizes the total energy of cluster. The remaining objects that have not been clustered are classified as noise. Then the parameter identification problem for the algorithm is considered. Preliminary results on clustering and parameter identification are obtained on several public test data sets.

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Acknowledgments

This research is conducted within the framework of the grant num. BR05236839 “Development of information technologies and systems for stimulation of personality’s sustainable development as one of the bases of development of digital Kazakhstan”.

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Authors and Affiliations

  1. Institute of Information and Computational Technologies, Pushkin str. 125, Almaty, Kazakhstan

    Alexander Krassovitskiy & Rustam Mussabayev

Authors
  1. Alexander Krassovitskiy
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  2. Rustam Mussabayev
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Corresponding author

Correspondence to Alexander Krassovitskiy .

Editor information

Editors and Affiliations

  1. Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Ngoc Thanh Nguyen

  2. Department of Computer Science and Creative Technologies, University of the West of England, Bristol, United Kingdom

    Elias Pimenidis

  3. Department of Computer Science and Creative Technologies, University of the West of England, Bristol, United Kingdom

    Zaheer Khan

  4. Faculty of Computer Science and Management, Wrocław University of Science and Technology, Wrocław, Poland

    Bogdan Trawiński

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Krassovitskiy, A., Mussabayev, R. (2018). Energy-Based Centroid Identification and Cluster Propagation with Noise Detection. In: Nguyen, N., Pimenidis, E., Khan, Z., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2018. Lecture Notes in Computer Science(), vol 11055. Springer, Cham. https://doi.org/10.1007/978-3-319-98443-8_48

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  • DOI: https://doi.org/10.1007/978-3-319-98443-8_48

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-98442-1

  • Online ISBN: 978-3-319-98443-8

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